Semantic Role Labeling of Clinical Text: Comparing Syntactic Parsers and Features

PubMed Central

Zhang, Yaoyun; Jiang, Min; Wang, Jingqi; Xu, Hua

2016-01-01

Semantic role labeling (SRL), which extracts shallow semantic relation representation from different surface textual forms of free text sentences, is important for understanding clinical narratives. Since semantic roles are formed by syntactic constituents in the sentence, an effective parser, as well as an effective syntactic feature set are essential to build a practical SRL system. Our study initiates a formal evaluation and comparison of SRL performance on a clinical text corpus MiPACQ, using three state-of-the-art parsers, the Stanford parser, the Berkeley parser, and the Charniak parser. First, the original parsers trained on the open domain syntactic corpus Penn Treebank were employed. Next, those parsers were retrained on the clinical Treebank of MiPACQ for further comparison. Additionally, state-of-the-art syntactic features from open domain SRL were also examined for clinical text. Experimental results showed that retraining the parsers on clinical Treebank improved the performance significantly, with an optimal F1 measure of 71.41% achieved by the Berkeley parser. PMID:28269926

"gnparser": a powerful parser for scientific names based on Parsing Expression Grammar.

PubMed

Mozzherin, Dmitry Y; Myltsev, Alexander A; Patterson, David J

2017-05-26

Scientific names in biology act as universal links. They allow us to cross-reference information about organisms globally. However variations in spelling of scientific names greatly diminish their ability to interconnect data. Such variations may include abbreviations, annotations, misspellings, etc. Authorship is a part of a scientific name and may also differ significantly. To match all possible variations of a name we need to divide them into their elements and classify each element according to its role. We refer to this as 'parsing' the name. Parsing categorizes name's elements into those that are stable and those that are prone to change. Names are matched first by combining them according to their stable elements. Matches are then refined by examining their varying elements. This two stage process dramatically improves the number and quality of matches. It is especially useful for the automatic data exchange within the context of "Big Data" in biology. We introduce Global Names Parser (gnparser). It is a Java tool written in Scala language (a language for Java Virtual Machine) to parse scientific names. It is based on a Parsing Expression Grammar. The parser can be applied to scientific names of any complexity. It assigns a semantic meaning (such as genus name, species epithet, rank, year of publication, authorship, annotations, etc.) to all elements of a name. It is able to work with nested structures as in the names of hybrids. gnparser performs with ≈99% accuracy and processes 30 million name-strings/hour per CPU thread. The gnparser library is compatible with Scala, Java, R, Jython, and JRuby. The parser can be used as a command line application, as a socket server, a web-app or as a RESTful HTTP-service. It is released under an Open source MIT license. Global Names Parser (gnparser) is a fast, high precision tool for biodiversity informaticians and biologists working with large numbers of scientific names. It can replace expensive and error

Intelligent Agents as a Basis for Natural Language Interfaces

DTIC Science & Technology

1988-01-01

language analysis component of UC, which produces a semantic representa tion of the input. This representation is in the form of a KODIAK network (see...Appendix A). Next, UC’s Concretion Mechanism performs concretion inferences ([Wilensky, 1983] and [Norvig, 1983]) based on the semantic network...The first step in UC’s processing is done by UC’s parser/understander component which produces a KODIAK semantic network representa tion of

Natural-Language Parser for PBEM

NASA Technical Reports Server (NTRS)

James, Mark

2010-01-01

A computer program called "Hunter" accepts, as input, a colloquial-English description of a set of policy-based-management rules, and parses that description into a form useable by policy-based enterprise management (PBEM) software. PBEM is a rules-based approach suitable for automating some management tasks. PBEM simplifies the management of a given enterprise through establishment of policies addressing situations that are likely to occur. Hunter was developed to have a unique capability to extract the intended meaning instead of focusing on parsing the exact ways in which individual words are used.

Storing files in a parallel computing system based on user-specified parser function

DOEpatents

Faibish, Sorin; Bent, John M; Tzelnic, Percy; Grider, Gary; Manzanares, Adam; Torres, Aaron

2014-10-21

Techniques are provided for storing files in a parallel computing system based on a user-specified parser function. A plurality of files generated by a distributed application in a parallel computing system are stored by obtaining a parser from the distributed application for processing the plurality of files prior to storage; and storing one or more of the plurality of files in one or more storage nodes of the parallel computing system based on the processing by the parser. The plurality of files comprise one or more of a plurality of complete files and a plurality of sub-files. The parser can optionally store only those files that satisfy one or more semantic requirements of the parser. The parser can also extract metadata from one or more of the files and the extracted metadata can be stored with one or more of the plurality of files and used for searching for files.

PDB file parser and structure class implemented in Python.

PubMed

Hamelryck, Thomas; Manderick, Bernard

2003-11-22

The biopython project provides a set of bioinformatics tools implemented in Python. Recently, biopython was extended with a set of modules that deal with macromolecular structure. Biopython now contains a parser for PDB files that makes the atomic information available in an easy-to-use but powerful data structure. The parser and data structure deal with features that are often left out or handled inadequately by other packages, e.g. atom and residue disorder (if point mutants are present in the crystal), anisotropic B factors, multiple models and insertion codes. In addition, the parser performs some sanity checking to detect obvious errors. The Biopython distribution (including source code and documentation) is freely available (under the Biopython license) from http://www.biopython.org

A python tool for the implementation of domain-specific languages

NASA Astrophysics Data System (ADS)

Dejanović, Igor; Vaderna, Renata; Milosavljević, Gordana; Simić, Miloš; Vuković, Željko

2017-07-01

In this paper we describe textX, a meta-language and a tool for building Domain-Specific Languages. It is implemented in Python using Arpeggio PEG (Parsing Expression Grammar) parser library. From a single language description (grammar) textX will build a parser and a meta-model (a.k.a. abstract syntax) of the language. The parser is used to parse textual representations of models conforming to the meta-model. As a result of parsing, a Python object graph will be automatically created. The structure of the object graph will conform to the meta-model defined by the grammar. This approach frees a developer from the need to manually analyse a parse tree and transform it to other suitable representation. The textX library is independent of any integrated development environment and can be easily integrated in any Python project. The textX tool works as a grammar interpreter. The parser is configured at run-time using the grammar. The textX tool is a free and open-source project available at GitHub.

Processing of ICARTT Data Files Using Fuzzy Matching and Parser Combinators

NASA Technical Reports Server (NTRS)

Rutherford, Matthew T.; Typanski, Nathan D.; Wang, Dali; Chen, Gao

2014-01-01

In this paper, the task of parsing and matching inconsistent, poorly formed text data through the use of parser combinators and fuzzy matching is discussed. An object-oriented implementation of the parser combinator technique is used to allow for a relatively simple interface for adapting base parsers. For matching tasks, a fuzzy matching algorithm with Levenshtein distance calculations is implemented to match string pair, which are otherwise difficult to match due to the aforementioned irregularities and errors in one or both pair members. Used in concert, the two techniques allow parsing and matching operations to be performed which had previously only been done manually.

GBParsy: a GenBank flatfile parser library with high speed.

PubMed

Lee, Tae-Ho; Kim, Yeon-Ki; Nahm, Baek Hie

2008-07-25

GenBank flatfile (GBF) format is one of the most popular sequence file formats because of its detailed sequence features and ease of readability. To use the data in the file by a computer, a parsing process is required and is performed according to a given grammar for the sequence and the description in a GBF. Currently, several parser libraries for the GBF have been developed. However, with the accumulation of DNA sequence information from eukaryotic chromosomes, parsing a eukaryotic genome sequence with these libraries inevitably takes a long time, due to the large GBF file and its correspondingly large genomic nucleotide sequence and related feature information. Thus, there is significant need to develop a parsing program with high speed and efficient use of system memory. We developed a library, GBParsy, which was C language-based and parses GBF files. The parsing speed was maximized by using content-specified functions in place of regular expressions that are flexible but slow. In addition, we optimized an algorithm related to memory usage so that it also increased parsing performance and efficiency of memory usage. GBParsy is at least 5-100x faster than current parsers in benchmark tests. GBParsy is estimated to extract annotated information from almost 100 Mb of a GenBank flatfile for chromosomal sequence information within a second. Thus, it should be used for a variety of applications such as on-time visualization of a genome at a web site.

Natural Language Processing.

ERIC Educational Resources Information Center

Chowdhury, Gobinda G.

2003-01-01

Discusses issues related to natural language processing, including theoretical developments; natural language understanding; tools and techniques; natural language text processing systems; abstracting; information extraction; information retrieval; interfaces; software; Internet, Web, and digital library applications; machine translation for…

A Protocol for Annotating Parser Differences. Research Report. ETS RR-16-02

ERIC Educational Resources Information Center

Bruno, James V.; Cahill, Aoife; Gyawali, Binod

2016-01-01

We present an annotation scheme for classifying differences in the outputs of syntactic constituency parsers when a gold standard is unavailable or undesired, as in the case of texts written by nonnative speakers of English. We discuss its automated implementation and the results of a case study that uses the scheme to choose a parser best suited…

Applying Semantic-based Probabilistic Context-Free Grammar to Medical Language Processing – A Preliminary Study on Parsing Medication Sentences

PubMed Central

Xu, Hua; AbdelRahman, Samir; Lu, Yanxin; Denny, Joshua C.; Doan, Son

2011-01-01

Semantic-based sublanguage grammars have been shown to be an efficient method for medical language processing. However, given the complexity of the medical domain, parsers using such grammars inevitably encounter ambiguous sentences, which could be interpreted by different groups of production rules and consequently result in two or more parse trees. One possible solution, which has not been extensively explored previously, is to augment productions in medical sublanguage grammars with probabilities to resolve the ambiguity. In this study, we associated probabilities with production rules in a semantic-based grammar for medication findings and evaluated its performance on reducing parsing ambiguity. Using the existing data set from 2009 i2b2 NLP (Natural Language Processing) challenge for medication extraction, we developed a semantic-based CFG (Context Free Grammar) for parsing medication sentences and manually created a Treebank of 4,564 medication sentences from discharge summaries. Using the Treebank, we derived a semantic-based PCFG (probabilistic Context Free Grammar) for parsing medication sentences. Our evaluation using a 10-fold cross validation showed that the PCFG parser dramatically improved parsing performance when compared to the CFG parser. PMID:21856440

ACPYPE - AnteChamber PYthon Parser interfacE.

PubMed

Sousa da Silva, Alan W; Vranken, Wim F

2012-07-23

ACPYPE (or AnteChamber PYthon Parser interfacE) is a wrapper script around the ANTECHAMBER software that simplifies the generation of small molecule topologies and parameters for a variety of molecular dynamics programmes like GROMACS, CHARMM and CNS. It is written in the Python programming language and was developed as a tool for interfacing with other Python based applications such as the CCPN software suite (for NMR data analysis) and ARIA (for structure calculations from NMR data). ACPYPE is open source code, under GNU GPL v3, and is available as a stand-alone application at http://www.ccpn.ac.uk/acpype and as a web portal application at http://webapps.ccpn.ac.uk/acpype. We verified the topologies generated by ACPYPE in three ways: by comparing with default AMBER topologies for standard amino acids; by generating and verifying topologies for a large set of ligands from the PDB; and by recalculating the structures for 5 protein-ligand complexes from the PDB. ACPYPE is a tool that simplifies the automatic generation of topology and parameters in different formats for different molecular mechanics programmes, including calculation of partial charges, while being object oriented for integration with other applications.

The Unification Space implemented as a localist neural net: predictions and error-tolerance in a constraint-based parser.

PubMed

Vosse, Theo; Kempen, Gerard

2009-12-01

We introduce a novel computer implementation of the Unification-Space parser (Vosse and Kempen in Cognition 75:105-143, 2000) in the form of a localist neural network whose dynamics is based on interactive activation and inhibition. The wiring of the network is determined by Performance Grammar (Kempen and Harbusch in Verb constructions in German and Dutch. Benjamins, Amsterdam, 2003), a lexicalist formalism with feature unification as binding operation. While the network is processing input word strings incrementally, the evolving shape of parse trees is represented in the form of changing patterns of activation in nodes that code for syntactic properties of words and phrases, and for the grammatical functions they fulfill. The system is capable, at least qualitatively and rudimentarily, of simulating several important dynamic aspects of human syntactic parsing, including garden-path phenomena and reanalysis, effects of complexity (various types of clause embeddings), fault-tolerance in case of unification failures and unknown words, and predictive parsing (expectation-based analysis, surprisal effects). English is the target language of the parser described.

Linking Parser Development to Acquisition of Syntactic Knowledge

ERIC Educational Resources Information Center

Omaki, Akira; Lidz, Jeffrey

2015-01-01

Traditionally, acquisition of syntactic knowledge and the development of sentence comprehension behaviors have been treated as separate disciplines. This article reviews a growing body of work on the development of incremental sentence comprehension mechanisms and discusses how a better understanding of the developing parser can shed light on two…

GazeParser: an open-source and multiplatform library for low-cost eye tracking and analysis.

PubMed

Sogo, Hiroyuki

2013-09-01

Eye movement analysis is an effective method for research on visual perception and cognition. However, recordings of eye movements present practical difficulties related to the cost of the recording devices and the programming of device controls for use in experiments. GazeParser is an open-source library for low-cost eye tracking and data analysis; it consists of a video-based eyetracker and libraries for data recording and analysis. The libraries are written in Python and can be used in conjunction with PsychoPy and VisionEgg experimental control libraries. Three eye movement experiments are reported on performance tests of GazeParser. These showed that the means and standard deviations for errors in sampling intervals were less than 1 ms. Spatial accuracy ranged from 0.7° to 1.2°, depending on participant. In gap/overlap tasks and antisaccade tasks, the latency and amplitude of the saccades detected by GazeParser agreed with those detected by a commercial eyetracker. These results showed that the GazeParser demonstrates adequate performance for use in psychological experiments.

Natural Language Sourcebook

DTIC Science & Technology

1990-01-01

Identification of Syntactic Units Exemplar I.A. (#l) Problem (1) The tough coach the young. (2) The tough coach married a star. (3) The tough coach married ...34the tough" vs. "the tough coach" and (b) "people" vs. " married people." The problem could also be considered a problem of determining lexical...and " married " in example (2). Once the parser specifies a verb, the structure of the rest of the sentence is determined: specifying "coach" as a

Towards automated processing of clinical Finnish: sublanguage analysis and a rule-based parser.

PubMed

Laippala, Veronika; Ginter, Filip; Pyysalo, Sampo; Salakoski, Tapio

2009-12-01

In this paper, we present steps taken towards more efficient automated processing of clinical Finnish, focusing on daily nursing notes in a Finnish Intensive Care Unit (ICU). First, we analyze ICU Finnish as a sublanguage, identifying its specific features facilitating, for example, the development of a specialized syntactic analyser. The identified features include frequent omission of finite verbs, limitations in allowed syntactic structures, and domain-specific vocabulary. Second, we develop a formal grammar and a parser for ICU Finnish, thus providing better tools for the development of further applications in the clinical domain. The grammar is implemented in the LKB system in a typed feature structure formalism. The lexicon is automatically generated based on the output of the FinTWOL morphological analyzer adapted to the clinical domain. As an additional experiment, we study the effect of using Finnish constraint grammar to reduce the size of the lexicon. The parser construction thus makes efficient use of existing resources for Finnish. The grammar currently covers 76.6% of ICU Finnish sentences, producing highly accurate best-parse analyzes with F-score of 91.1%. We find that building a parser for the highly specialized domain sublanguage is not only feasible, but also surprisingly efficient, given an existing morphological analyzer with broad vocabulary coverage. The resulting parser enables a deeper analysis of the text than was previously possible.

The parser doesn't ignore intransitivity, after all

PubMed Central

Staub, Adrian

2015-01-01

Several previous studies (Adams, Clifton, & Mitchell, 1998; Mitchell, 1987; van Gompel & Pickering, 2001) have explored the question of whether the parser initially analyzes a noun phrase that follows an intransitive verb as the verb's direct object. Three eyetracking experiments examined this issue in more detail. Experiment 1 strongly replicated the finding (van Gompel & Pickering, 2001) that readers experience difficulty on this noun phrase in normal reading, and found that this difficulty occurs even with a class of intransitive verbs for which a direct object is categorically prohibited. Experiment 2, however, demonstrated that this effect is not due to syntactic misanalysis, but is instead due to disruption that occurs when a comma is absent at a subordinate clause/main clause boundary. Exploring a different construction, Experiment 3 replicated the finding (Pickering & Traxler, 2003; Traxler & Pickering, 1996) that when a noun phrase “filler” is an implausible direct object for an optionally transitive relative clause verb, processing difficulty results; however, there was no evidence for such difficulty when the relative clause verb was strictly intransitive. Taken together, the three experiments undermine the support for the claim that the parser initially ignores a verb's subcategorization restrictions. PMID:17470005

Software Development Of XML Parser Based On Algebraic Tools

NASA Astrophysics Data System (ADS)

Georgiev, Bozhidar; Georgieva, Adriana

2011-12-01

In this paper, is presented one software development and implementation of an algebraic method for XML data processing, which accelerates XML parsing process. Therefore, the proposed in this article nontraditional approach for fast XML navigation with algebraic tools contributes to advanced efforts in the making of an easier user-friendly API for XML transformations. Here the proposed software for XML documents processing (parser) is easy to use and can manage files with strictly defined data structure. The purpose of the presented algorithm is to offer a new approach for search and restructuring hierarchical XML data. This approach permits fast XML documents processing, using algebraic model developed in details in previous works of the same authors. So proposed parsing mechanism is easy accessible to the web consumer who is able to control XML file processing, to search different elements (tags) in it, to delete and to add a new XML content as well. The presented various tests show higher rapidity and low consumption of resources in comparison with some existing commercial parsers.

MASCOT HTML and XML parser: an implementation of a novel object model for protein identification data.

PubMed

Yang, Chunguang G; Granite, Stephen J; Van Eyk, Jennifer E; Winslow, Raimond L

2006-11-01

Protein identification using MS is an important technique in proteomics as well as a major generator of proteomics data. We have designed the protein identification data object model (PDOM) and developed a parser based on this model to facilitate the analysis and storage of these data. The parser works with HTML or XML files saved or exported from MASCOT MS/MS ions search in peptide summary report or MASCOT PMF search in protein summary report. The program creates PDOM objects, eliminates redundancy in the input file, and has the capability to output any PDOM object to a relational database. This program facilitates additional analysis of MASCOT search results and aids the storage of protein identification information. The implementation is extensible and can serve as a template to develop parsers for other search engines. The parser can be used as a stand-alone application or can be driven by other Java programs. It is currently being used as the front end for a system that loads HTML and XML result files of MASCOT searches into a relational database. The source code is freely available at http://www.ccbm.jhu.edu and the program uses only free and open-source Java libraries.

Programming Languages, Natural Languages, and Mathematics

ERIC Educational Resources Information Center

Naur, Peter

1975-01-01

Analogies are drawn between the social aspects of programming and similar aspects of mathematics and natural languages. By analogy with the history of auxiliary languages it is suggested that Fortran and Cobol will remain dominant. (Available from the Association of Computing Machinery, 1133 Avenue of the Americas, New York, NY 10036.) (Author/TL)

ImageParser: a tool for finite element generation from three-dimensional medical images

PubMed Central

Yin, HM; Sun, LZ; Wang, G; Yamada, T; Wang, J; Vannier, MW

2004-01-01

Background The finite element method (FEM) is a powerful mathematical tool to simulate and visualize the mechanical deformation of tissues and organs during medical examinations or interventions. It is yet a challenge to build up an FEM mesh directly from a volumetric image partially because the regions (or structures) of interest (ROIs) may be irregular and fuzzy. Methods A software package, ImageParser, is developed to generate an FEM mesh from 3-D tomographic medical images. This software uses a semi-automatic method to detect ROIs from the context of image including neighboring tissues and organs, completes segmentation of different tissues, and meshes the organ into elements. Results The ImageParser is shown to build up an FEM model for simulating the mechanical responses of the breast based on 3-D CT images. The breast is compressed by two plate paddles under an overall displacement as large as 20% of the initial distance between the paddles. The strain and tangential Young's modulus distributions are specified for the biomechanical analysis of breast tissues. Conclusion The ImageParser can successfully exact the geometry of ROIs from a complex medical image and generate the FEM mesh with customer-defined segmentation information. PMID:15461787

Adding a Medical Lexicon to an English Parser

PubMed Central

Szolovits, Peter

2003-01-01

We present a heuristic method to map lexical (syntactic) information from one lexicon to another, and apply the technique to augment the lexicon of the Link Grammar Parser with an enormous medical vocabulary drawn from the Specialist lexicon developed by the National Library of Medicine. This paper presents and justifies the mapping method and addresses technical problems that have to be overcome. It illustrates the utility of the method with respect to a large corpus of emergency department notes. PMID:14728251

Natural language modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sharp, J.K.

1997-11-01

This seminar describes a process and methodology that uses structured natural language to enable the construction of precise information requirements directly from users, experts, and managers. The main focus of this natural language approach is to create the precise information requirements and to do it in such a way that the business and technical experts are fully accountable for the results. These requirements can then be implemented using appropriate tools and technology. This requirement set is also a universal learning tool because it has all of the knowledge that is needed to understand a particular process (e.g., expense vouchers, projectmore » management, budget reviews, tax, laws, machine function).« less

ULTRA: Universal Grammar as a Universal Parser

PubMed Central

Medeiros, David P.

2018-01-01

A central concern of generative grammar is the relationship between hierarchy and word order, traditionally understood as two dimensions of a single syntactic representation. A related concern is directionality in the grammar. Traditional approaches posit process-neutral grammars, embodying knowledge of language, put to use with infinite facility both for production and comprehension. This has crystallized in the view of Merge as the central property of syntax, perhaps its only novel feature. A growing number of approaches explore grammars with different directionalities, often with more direct connections to performance mechanisms. This paper describes a novel model of universal grammar as a one-directional, universal parser. Mismatch between word order and interpretation order is pervasive in comprehension; in the present model, word order is language-particular and interpretation order (i.e., hierarchy) is universal. These orders are not two dimensions of a unified abstract object (e.g., precedence and dominance in a single tree); rather, both are temporal sequences, and UG is an invariant real-time procedure (based on Knuth's stack-sorting algorithm) transforming word order into hierarchical order. This shift in perspective has several desirable consequences. It collapses linearization, displacement, and composition into a single performance process. The architecture provides a novel source of brackets (labeled unambiguously and without search), which are understood not as part-whole constituency relations, but as storage and retrieval routines in parsing. It also explains why neutral word order within single syntactic cycles avoids 213-like permutations. The model identifies cycles as extended projections of lexical heads, grounding the notion of phase. This is achieved with a universal processor, dispensing with parameters. The empirical focus is word order in noun phrases. This domain provides some of the clearest evidence for 213-avoidance as a cross

Grammar as a Programming Language. Artificial Intelligence Memo 391.

ERIC Educational Resources Information Center

Rowe, Neil

Student projects that involve writing generative grammars in the computer language, "LOGO," are described in this paper, which presents a grammar-running control structure that allows students to modify and improve the grammar interpreter itself while learning how a simple kind of computer parser works. Included are procedures for…

Integrated Intelligence: Robot Instruction via Interactive Grounded Learning

DTIC Science & Technology

2016-02-14

ADDRESS (ES) U.S. Army Research Office P.O. Box 12211 Research Triangle Park, NC 27709-2211 Robotics; Natural Language Processing ; Grounded Language ...Logical Forms for Referring Expression Generation, Emperical Methods in Natural Language Processing (EMNLP). 18-OCT-13, . : , Tom Kwiatkowska, Eunsol...Choi, Yoav Artzi, Luke Zettlemoyer. Scaling Semantic Parsers with On-the-fly Ontology Matching, Emperical Methods in Natural Langauge Processing

Natural language generation of surgical procedures.

PubMed

Wagner, J C; Rogers, J E; Baud, R H; Scherrer, J R

1999-01-01

A number of compositional Medical Concept Representation systems are being developed. Although these provide for a detailed conceptual representation of the underlying information, they have to be translated back to natural language for used by end-users and applications. The GALEN programme has been developing one such representation and we report here on a tool developed to generate natural language phrases from the GALEN conceptual representations. This tool can be adapted to different source modelling schemes and to different destination languages or sublanguages of a domain. It is based on a multilingual approach to natural language generation, realised through a clean separation of the domain model from the linguistic model and their link by well defined structures. Specific knowledge structures and operations have been developed for bridging between the modelling 'style' of the conceptual representation and natural language. Using the example of the scheme developed for modelling surgical operative procedures within the GALEN-IN-USE project, we show how the generator is adapted to such a scheme. The basic characteristics of the surgical procedures scheme are presented together with the basic principles of the generation tool. Using worked examples, we discuss the transformation operations which change the initial source representation into a form which can more directly be translated to a given natural language. In particular, the linguistic knowledge which has to be introduced--such as definitions of concepts and relationships is described. We explain the overall generator strategy and how particular transformation operations are triggered by language-dependent and conceptual parameters. Results are shown for generated French phrases corresponding to surgical procedures from the urology domain.

Natural Language Processing: Toward Large-Scale, Robust Systems.

ERIC Educational Resources Information Center

Haas, Stephanie W.

1996-01-01

Natural language processing (NLP) is concerned with getting computers to do useful things with natural language. Major applications include machine translation, text generation, information retrieval, and natural language interfaces. Reviews important developments since 1987 that have led to advances in NLP; current NLP applications; and problems…

Natural language generation of surgical procedures.

PubMed

Wagner, J C; Rogers, J E; Baud, R H; Scherrer, J R

1998-01-01

The GALEN-IN-USE project has developed a compositional scheme for the conceptual representation of surgical operative procedure rubrics. The complex representations which result are translated back to surface language by a tool for multilingual natural language generation. This generator can be adapted to the specific characteristics of the scheme by introducing particular definitions of concepts and relationships. We discuss how the generator uses such definitions to bridge between the modelling 'style' of the GALEN scheme and natural language.

Thermo-msf-parser: an open source Java library to parse and visualize Thermo Proteome Discoverer msf files.

PubMed

Colaert, Niklaas; Barsnes, Harald; Vaudel, Marc; Helsens, Kenny; Timmerman, Evy; Sickmann, Albert; Gevaert, Kris; Martens, Lennart

2011-08-05

The Thermo Proteome Discoverer program integrates both peptide identification and quantification into a single workflow for peptide-centric proteomics. Furthermore, its close integration with Thermo mass spectrometers has made it increasingly popular in the field. Here, we present a Java library to parse the msf files that constitute the output of Proteome Discoverer. The parser is also implemented as a graphical user interface allowing convenient access to the information found in the msf files, and in Rover, a program to analyze and validate quantitative proteomics information. All code, binaries, and documentation is freely available at http://thermo-msf-parser.googlecode.com.

Thought beyond language: neural dissociation of algebra and natural language.

PubMed

Monti, Martin M; Parsons, Lawrence M; Osherson, Daniel N

2012-08-01

A central question in cognitive science is whether natural language provides combinatorial operations that are essential to diverse domains of thought. In the study reported here, we addressed this issue by examining the role of linguistic mechanisms in forging the hierarchical structures of algebra. In a 3-T functional MRI experiment, we showed that processing of the syntax-like operations of algebra does not rely on the neural mechanisms of natural language. Our findings indicate that processing the syntax of language elicits the known substrate of linguistic competence, whereas algebraic operations recruit bilateral parietal brain regions previously implicated in the representation of magnitude. This double dissociation argues against the view that language provides the structure of thought across all cognitive domains.

The nature of the language input affects brain activation during learning from a natural language

PubMed Central

Plante, Elena; Patterson, Dianne; Gómez, Rebecca; Almryde, Kyle R.; White, Milo G.; Asbjørnsen, Arve E.

2015-01-01

Artificial language studies have demonstrated that learners are able to segment individual word-like units from running speech using the transitional probability information. However, this skill has rarely been examined in the context of natural languages, where stimulus parameters can be quite different. In this study, two groups of English-speaking learners were exposed to Norwegian sentences over the course of three fMRI scans. One group was provided with input in which transitional probabilities predicted the presence of target words in the sentences. This group quickly learned to identify the target words and fMRI data revealed an extensive and highly dynamic learning network. These results were markedly different from activation seen for a second group of participants. This group was provided with highly similar input that was modified so that word learning based on syllable co-occurrences was not possible. These participants showed a much more restricted network. The results demonstrate that the nature of the input strongly influenced the nature of the network that learners employ to learn the properties of words in a natural language. PMID:26257471

Research in Knowledge Representation for Natural Language Understanding.

DTIC Science & Technology

1984-09-01

TYPE OF REPORT & PERIOO COVERED RESEARCH IN KNOWLEDGE REPRESENTATION Annual Report FOR NATURAL LANGUAGE UNDERSTANDING 9/1/83 - 8/31/84 S. PERFORMING...nhaber) Artificial intelligence, natural language understanding , knowledge representation, semantics, semantic networks, KL-TWO, NIKL, belief and...attempting to understand and react to a complex, evolving situation. This report summarizes our research in knowledge representation and natural language

Natural language interface for command and control

NASA Technical Reports Server (NTRS)

Shuler, Robert L., Jr.

1986-01-01

A working prototype of a flexible 'natural language' interface for command and control situations is presented. This prototype is analyzed from two standpoints. First is the role of natural language for command and control, its realistic requirements, and how well the role can be filled with current practical technology. Second, technical concepts for implementation are discussed and illustrated by their application in the prototype system. It is also shown how adaptive or 'learning' features can greatly ease the task of encoding language knowledge in the language processor.

Integration of Speech and Natural Language

DTIC Science & Technology

1988-04-01

major activities: • Development of the syntax and semantics components for natural language processing. • Integration of the developed syntax and...evaluating the performance of speech recognition algonthms developed K» under the Strategic Computing Program. grs Our work on natural language processing...included the developement of a grammar (syntax) that uses the Uiuficanon gnmmaj formaMsm (an augmented context free formalism). The Unification

An Overview of Computer-Based Natural Language Processing.

ERIC Educational Resources Information Center

Gevarter, William B.

Computer-based Natural Language Processing (NLP) is the key to enabling humans and their computer-based creations to interact with machines using natural languages (English, Japanese, German, etc.) rather than formal computer languages. NLP is a major research area in the fields of artificial intelligence and computational linguistics. Commercial…

Survey of Natural Language Processing Techniques in Bioinformatics.

PubMed

Zeng, Zhiqiang; Shi, Hua; Wu, Yun; Hong, Zhiling

2015-01-01

Informatics methods, such as text mining and natural language processing, are always involved in bioinformatics research. In this study, we discuss text mining and natural language processing methods in bioinformatics from two perspectives. First, we aim to search for knowledge on biology, retrieve references using text mining methods, and reconstruct databases. For example, protein-protein interactions and gene-disease relationship can be mined from PubMed. Then, we analyze the applications of text mining and natural language processing techniques in bioinformatics, including predicting protein structure and function, detecting noncoding RNA. Finally, numerous methods and applications, as well as their contributions to bioinformatics, are discussed for future use by text mining and natural language processing researchers.

Computational Natural Language Inference: Robust and Interpretable Question Answering

ERIC Educational Resources Information Center

Sharp, Rebecca Reynolds

2017-01-01

We address the challenging task of "computational natural language inference," by which we mean bridging two or more natural language texts while also providing an explanation of how they are connected. In the context of question answering (i.e., finding short answers to natural language questions), this inference connects the question…

Extracting noun phrases for all of MEDLINE.

PubMed Central

Bennett, N. A.; He, Q.; Powell, K.; Schatz, B. R.

1999-01-01

A natural language parser that could extract noun phrases for all medical texts would be of great utility in analyzing content for information retrieval. We discuss the extraction of noun phrases from MEDLINE, using a general parser not tuned specifically for any medical domain. The noun phrase extractor is made up of three modules: tokenization; part-of-speech tagging; noun phrase identification. Using our program, we extracted noun phrases from the entire MEDLINE collection, encompassing 9.3 million abstracts. Over 270 million noun phrases were generated, of which 45 million were unique. The quality of these phrases was evaluated by examining all phrases from a sample collection of abstracts. The precision and recall of the phrases from our general parser compared favorably with those from three other parsers we had previously evaluated. We are continuing to improve our parser and evaluate our claim that a generic parser can effectively extract all the different phrases across the entire medical literature. PMID:10566444

Parsley: a Command-Line Parser for Astronomical Applications

NASA Astrophysics Data System (ADS)

Deich, William

Parsley is a sophisticated keyword + value parser, packaged as a library of routines that offers an easy method for providing command-line arguments to programs. It makes it easy for the user to enter values, and it makes it easy for the programmer to collect and validate the user's entries. Parsley is tuned for astronomical applications: for example, dates entered in Julian, Modified Julian, calendar, or several other formats are all recognized without special effort by the user or by the programmer; angles can be entered using decimal degrees or dd:mm:ss; time-like intervals as decimal hours, hh:mm:ss, or a variety of other units. Vectors of data are accepted as readily as scalars.

Advances in natural language processing.

PubMed

Hirschberg, Julia; Manning, Christopher D

2015-07-17

Natural language processing employs computational techniques for the purpose of learning, understanding, and producing human language content. Early computational approaches to language research focused on automating the analysis of the linguistic structure of language and developing basic technologies such as machine translation, speech recognition, and speech synthesis. Today's researchers refine and make use of such tools in real-world applications, creating spoken dialogue systems and speech-to-speech translation engines, mining social media for information about health or finance, and identifying sentiment and emotion toward products and services. We describe successes and challenges in this rapidly advancing area. Copyright © 2015, American Association for the Advancement of Science.

DBPQL: A view-oriented query language for the Intel Data Base Processor

NASA Technical Reports Server (NTRS)

Fishwick, P. A.

1983-01-01

An interactive query language (BDPQL) for the Intel Data Base Processor (DBP) is defined. DBPQL includes a parser generator package which permits the analyst to easily create and manipulate the query statement syntax and semantics. The prototype language, DBPQL, includes trace and performance commands to aid the analyst when implementing new commands and analyzing the execution characteristics of the DBP. The DBPQL grammar file and associated key procedures are included as an appendix to this report.

Linguistic Analysis of Natural Language Communication with Computers.

ERIC Educational Resources Information Center

Thompson, Bozena Henisz

Interaction with computers in natural language requires a language that is flexible and suited to the task. This study of natural dialogue was undertaken to reveal those characteristics which can make computer English more natural. Experiments were made in three modes of communication: face-to-face, terminal-to-terminal, and human-to-computer,…

Expressing Biomedical Ontologies in Natural Language for Expert Evaluation.

PubMed

Amith, Muhammad; Manion, Frank J; Harris, Marcelline R; Zhang, Yaoyun; Xu, Hua; Tao, Cui

2017-01-01

We report on a study of our custom Hootation software for the purposes of assessing its ability to produce clear and accurate natural language phrases from axioms embedded in three biomedical ontologies. Using multiple domain experts and three discrete rating scales, we evaluated the tool on clarity of the natural language produced, fidelity of the natural language produced from the ontology to the axiom, and the fidelity of the domain knowledge represented by the axioms. Results show that Hootation provided relatively clear natural language equivalents for a select set of OWL axioms, although the clarity of statements hinges on the accuracy and representation of axioms in the ontology.

Bibliography of Research in Natural Language Generation

DTIC Science & Technology

1993-11-01

on 1397] Barbara J. Gross Focuing and description in Artifcial Intelligence (GWAI-88), Geseke, West natural language dialogues, In Joshi et al. (557...Proceedings of the Fifth Canadian Conference from information in a frame structure. Data and on Artificial Intelligence , pages Ŕ-24, London, Knowledge...generation workshops (IWNLGS, ENLGWS), natural language processing conferences (ANLP, TINLAP, SPEECH), artificial intelligence conferences (AAAI, SCA

Speed up of XML parsers with PHP language implementation

NASA Astrophysics Data System (ADS)

Georgiev, Bozhidar; Georgieva, Adriana

2012-11-01

In this paper, authors introduce PHP5's XML implementation and show how to read, parse, and write a short and uncomplicated XML file using Simple XML in a PHP environment. The possibilities for mutual work of PHP5 language and XML standard are described. The details of parsing process with Simple XML are also cleared. A practical project PHP-XML-MySQL presents the advantages of XML implementation in PHP modules. This approach allows comparatively simple search of XML hierarchical data by means of PHP software tools. The proposed project includes database, which can be extended with new data and new XML parsing functions.

Semantic based man-machine interface for real-time communication

NASA Technical Reports Server (NTRS)

Ali, M.; Ai, C.-S.

1988-01-01

A flight expert system (FLES) was developed to assist pilots in monitoring, diagnosing and recovering from in-flight faults. To provide a communications interface between the flight crew and FLES, a natural language interface (NALI) was implemented. Input to NALI is processed by three processors: (1) the semantics parser; (2) the knowledge retriever; and (3) the response generator. First the semantic parser extracts meaningful words and phrases to generate an internal representation of the query. At this point, the semantic parser has the ability to map different input forms related to the same concept into the same internal representation. Then the knowledge retriever analyzes and stores the context of the query to aid in resolving ellipses and pronoun references. At the end of this process, a sequence of retrievel functions is created as a first step in generating the proper response. Finally, the response generator generates the natural language response to the query. The architecture of NALI was designed to process both temporal and nontemporal queries. The architecture and implementation of NALI are described.

Do neural nets learn statistical laws behind natural language?

PubMed

Takahashi, Shuntaro; Tanaka-Ishii, Kumiko

2017-01-01

The performance of deep learning in natural language processing has been spectacular, but the reasons for this success remain unclear because of the inherent complexity of deep learning. This paper provides empirical evidence of its effectiveness and of a limitation of neural networks for language engineering. Precisely, we demonstrate that a neural language model based on long short-term memory (LSTM) effectively reproduces Zipf's law and Heaps' law, two representative statistical properties underlying natural language. We discuss the quality of reproducibility and the emergence of Zipf's law and Heaps' law as training progresses. We also point out that the neural language model has a limitation in reproducing long-range correlation, another statistical property of natural language. This understanding could provide a direction for improving the architectures of neural networks.

Do neural nets learn statistical laws behind natural language?

PubMed Central

Takahashi, Shuntaro

2017-01-01

The performance of deep learning in natural language processing has been spectacular, but the reasons for this success remain unclear because of the inherent complexity of deep learning. This paper provides empirical evidence of its effectiveness and of a limitation of neural networks for language engineering. Precisely, we demonstrate that a neural language model based on long short-term memory (LSTM) effectively reproduces Zipf’s law and Heaps’ law, two representative statistical properties underlying natural language. We discuss the quality of reproducibility and the emergence of Zipf’s law and Heaps’ law as training progresses. We also point out that the neural language model has a limitation in reproducing long-range correlation, another statistical property of natural language. This understanding could provide a direction for improving the architectures of neural networks. PMID:29287076

Clinical Natural Language Processing in languages other than English: opportunities and challenges.

PubMed

Névéol, Aurélie; Dalianis, Hercules; Velupillai, Sumithra; Savova, Guergana; Zweigenbaum, Pierre

2018-03-30

Natural language processing applied to clinical text or aimed at a clinical outcome has been thriving in recent years. This paper offers the first broad overview of clinical Natural Language Processing (NLP) for languages other than English. Recent studies are summarized to offer insights and outline opportunities in this area. We envision three groups of intended readers: (1) NLP researchers leveraging experience gained in other languages, (2) NLP researchers faced with establishing clinical text processing in a language other than English, and (3) clinical informatics researchers and practitioners looking for resources in their languages in order to apply NLP techniques and tools to clinical practice and/or investigation. We review work in clinical NLP in languages other than English. We classify these studies into three groups: (i) studies describing the development of new NLP systems or components de novo, (ii) studies describing the adaptation of NLP architectures developed for English to another language, and (iii) studies focusing on a particular clinical application. We show the advantages and drawbacks of each method, and highlight the appropriate application context. Finally, we identify major challenges and opportunities that will affect the impact of NLP on clinical practice and public health studies in a context that encompasses English as well as other languages.

A Natural Language Interface Concordant with a Knowledge Base.

PubMed

Han, Yong-Jin; Park, Seong-Bae; Park, Se-Young

2016-01-01

The discordance between expressions interpretable by a natural language interface (NLI) system and those answerable by a knowledge base is a critical problem in the field of NLIs. In order to solve this discordance problem, this paper proposes a method to translate natural language questions into formal queries that can be generated from a graph-based knowledge base. The proposed method considers a subgraph of a knowledge base as a formal query. Thus, all formal queries corresponding to a concept or a predicate in the knowledge base can be generated prior to query time and all possible natural language expressions corresponding to each formal query can also be collected in advance. A natural language expression has a one-to-one mapping with a formal query. Hence, a natural language question is translated into a formal query by matching the question with the most appropriate natural language expression. If the confidence of this matching is not sufficiently high the proposed method rejects the question and does not answer it. Multipredicate queries are processed by regarding them as a set of collected expressions. The experimental results show that the proposed method thoroughly handles answerable questions from the knowledge base and rejects unanswerable ones effectively.

Concepts and implementations of natural language query systems

NASA Technical Reports Server (NTRS)

Dominick, Wayne D. (Editor); Liu, I-Hsiung

1984-01-01

The currently developed user language interfaces of information systems are generally intended for serious users. These interfaces commonly ignore potentially the largest user group, i.e., casual users. This project discusses the concepts and implementations of a natural query language system which satisfy the nature and information needs of casual users by allowing them to communicate with the system in the form of their native (natural) language. In addition, a framework for the development of such an interface is also introduced for the MADAM (Multics Approach to Data Access and Management) system at the University of Southwestern Louisiana.

Natural language processing, pragmatics, and verbal behavior

PubMed Central

Cherpas, Chris

1992-01-01

Natural Language Processing (NLP) is that part of Artificial Intelligence (AI) concerned with endowing computers with verbal and listener repertoires, so that people can interact with them more easily. Most attention has been given to accurately parsing and generating syntactic structures, although NLP researchers are finding ways of handling the semantic content of language as well. It is increasingly apparent that understanding the pragmatic (contextual and consequential) dimension of natural language is critical for producing effective NLP systems. While there are some techniques for applying pragmatics in computer systems, they are piecemeal, crude, and lack an integrated theoretical foundation. Unfortunately, there is little awareness that Skinner's (1957) Verbal Behavior provides an extensive, principled pragmatic analysis of language. The implications of Skinner's functional analysis for NLP and for verbal aspects of epistemology lead to a proposal for a “user expert”—a computer system whose area of expertise is the long-term computer user. The evolutionary nature of behavior suggests an AI technology known as genetic algorithms/programming for implementing such a system. ImagesFig. 1 PMID:22477052

Development of clinical contents model markup language for electronic health records.

PubMed

Yun, Ji-Hyun; Ahn, Sun-Ju; Kim, Yoon

2012-09-01

To develop dedicated markup language for clinical contents models (CCM) to facilitate the active use of CCM in electronic health record systems. Based on analysis of the structure and characteristics of CCM in the clinical domain, we designed extensible markup language (XML) based CCM markup language (CCML) schema manually. CCML faithfully reflects CCM in both the syntactic and semantic aspects. As this language is based on XML, it can be expressed and processed in computer systems and can be used in a technology-neutral way. CCML HAS THE FOLLOWING STRENGTHS: it is machine-readable and highly human-readable, it does not require a dedicated parser, and it can be applied for existing electronic health record systems.

An overview of computer-based natural language processing

NASA Technical Reports Server (NTRS)

Gevarter, W. B.

1983-01-01

Computer based Natural Language Processing (NLP) is the key to enabling humans and their computer based creations to interact with machines in natural language (like English, Japanese, German, etc., in contrast to formal computer languages). The doors that such an achievement can open have made this a major research area in Artificial Intelligence and Computational Linguistics. Commercial natural language interfaces to computers have recently entered the market and future looks bright for other applications as well. This report reviews the basic approaches to such systems, the techniques utilized, applications, the state of the art of the technology, issues and research requirements, the major participants and finally, future trends and expectations. It is anticipated that this report will prove useful to engineering and research managers, potential users, and others who will be affected by this field as it unfolds.

A natural command language for C/3/I applications

NASA Astrophysics Data System (ADS)

Mergler, J. P.

1980-03-01

The article discusses the development of a natural command language and a control and analysis console designed to simplify the task of the operator in field of Command, Control, Communications, and Intelligence. The console is based on a DEC LSI-11 microcomputer, supported by 16-K words of memory and a serial interface component. Discussion covers the language, which utilizes English and a natural syntax, and how it is integrated with the hardware. It is concluded that results have demonstrated the effectiveness of this natural command language.

A translator writing system for microcomputer high-level languages and assemblers

NASA Technical Reports Server (NTRS)

Collins, W. R.; Knight, J. C.; Noonan, R. E.

1980-01-01

In order to implement high level languages whenever possible, a translator writing system of advanced design was developed. It is intended for routine production use by many programmers working on different projects. As well as a fairly conventional parser generator, it includes a system for the rapid generation of table driven code generators. The parser generator was developed from a prototype version. The translator writing system includes various tools for the management of the source text of a compiler under construction. In addition, it supplies various default source code sections so that its output is always compilable and executable. The system thereby encourages iterative enhancement as a development methodology by ensuring an executable program from the earliest stages of a compiler development project. The translator writing system includes PASCAL/48 compiler, three assemblers, and two compilers for a subset of HAL/S.

L3 Interactive Data Language

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hohn, Michael; Adams, Paul

2006-09-05

The L3 system is a computational steering environment for image processing and scientific computing. It consists of an interactive graphical language and interface. Its purpose is to help advanced users in controlling their computational software and assist in the management of data accumulated during numerical experiments. L3 provides a combination of features not found in other environments; these are: - textual and graphical construction of programs - persistence of programs and associated data - direct mapping between the scripts, the parameters, and the produced data - implicit hierarchial data organization - full programmability, including conditionals and functions - incremental executionmore » of programs The software includes the l3 language and the graphical environment. The language is a single-assignment functional language; the implementation consists of lexer, parser, interpreter, storage handler, and editing support, The graphical environment is an event-driven nested list viewer/editor providing graphical elements corresponding to the language. These elements are both the represenation of a users program and active interfaces to the values computed by that program.« less

Inferring heuristic classification hierarchies from natural language input

NASA Technical Reports Server (NTRS)

Hull, Richard; Gomez, Fernando

1993-01-01

A methodology for inferring hierarchies representing heuristic knowledge about the check out, control, and monitoring sub-system (CCMS) of the space shuttle launch processing system from natural language input is explained. Our method identifies failures explicitly and implicitly described in natural language by domain experts and uses those descriptions to recommend classifications for inclusion in the experts' heuristic hierarchies.

Generating and Executing Complex Natural Language Queries across Linked Data.

PubMed

Hamon, Thierry; Mougin, Fleur; Grabar, Natalia

2015-01-01

With the recent and intensive research in the biomedical area, the knowledge accumulated is disseminated through various knowledge bases. Links between these knowledge bases are needed in order to use them jointly. Linked Data, SPARQL language, and interfaces in Natural Language question-answering provide interesting solutions for querying such knowledge bases. We propose a method for translating natural language questions in SPARQL queries. We use Natural Language Processing tools, semantic resources, and the RDF triples description. The method is designed on 50 questions over 3 biomedical knowledge bases, and evaluated on 27 questions. It achieves 0.78 F-measure on the test set. The method for translating natural language questions into SPARQL queries is implemented as Perl module available at http://search.cpan.org/ thhamon/RDF-NLP-SPARQLQuery.

Intelligent CAI: An Author Aid for a Natural Language Interface.

ERIC Educational Resources Information Center

Burton, Richard R.; Brown, John Seely

This report addresses the problems of using natural language (English) as the communication language for advanced computer-based instructional systems. The instructional environment places requirements on a natural language understanding system that exceed the capabilities of all existing systems, including: (1) efficiency, (2) habitability, (3)…

Errors and Intelligence in Computer-Assisted Language Learning: Parsers and Pedagogues. Routledge Studies in Computer Assisted Language Learning

ERIC Educational Resources Information Center

Heift, Trude; Schulze, Mathias

2012-01-01

This book provides the first comprehensive overview of theoretical issues, historical developments and current trends in ICALL (Intelligent Computer-Assisted Language Learning). It assumes a basic familiarity with Second Language Acquisition (SLA) theory and teaching, CALL and linguistics. It is of interest to upper undergraduate and/or graduate…

Automatic Requirements Specification Extraction from Natural Language (ARSENAL)

DTIC Science & Technology

2014-10-01

designers, implementers) involved in the design of software systems. However, natural language descriptions can be informal, incomplete, imprecise...communication of technical descriptions between the various stakeholders (e.g., customers, designers, imple- menters) involved in the design of software systems...the accuracy of the natural language processing stage, the degree of automation, and robustness to noise. 1 2 Introduction Software systems operate in

Research in Knowledge Representation for Natural Language Understanding

DTIC Science & Technology

1980-11-01

artificial intelligence, natural language understanding , parsing, syntax, semantics, speaker meaning, knowledge representation, semantic networks...TinB PAGE map M W006 1Report No. 4513 L RESEARCH IN KNOWLEDGE REPRESENTATION FOR NATURAL LANGUAGE UNDERSTANDING Annual Report 1 September 1979 to 31... understanding , knowledge representation, and knowledge based inference. The work that we have been doing falls into three classes, successively motivated by

A grammar-based semantic similarity algorithm for natural language sentences.

PubMed

Lee, Ming Che; Chang, Jia Wei; Hsieh, Tung Cheng

2014-01-01

This paper presents a grammar and semantic corpus based similarity algorithm for natural language sentences. Natural language, in opposition to "artificial language", such as computer programming languages, is the language used by the general public for daily communication. Traditional information retrieval approaches, such as vector models, LSA, HAL, or even the ontology-based approaches that extend to include concept similarity comparison instead of cooccurrence terms/words, may not always determine the perfect matching while there is no obvious relation or concept overlap between two natural language sentences. This paper proposes a sentence similarity algorithm that takes advantage of corpus-based ontology and grammatical rules to overcome the addressed problems. Experiments on two famous benchmarks demonstrate that the proposed algorithm has a significant performance improvement in sentences/short-texts with arbitrary syntax and structure.

A System for Natural Language Sentence Generation.

ERIC Educational Resources Information Center

Levison, Michael; Lessard, Gregory

1992-01-01

Describes the natural language computer program, "Vinci." Explains that using an attribute grammar formalism, Vinci can simulate components of several current linguistic theories. Considers the design of the system and its applications in linguistic modelling and second language acquisition research. Notes Vinci's uses in linguistics…

Neural Network Computing and Natural Language Processing.

ERIC Educational Resources Information Center

Borchardt, Frank

1988-01-01

Considers the application of neural network concepts to traditional natural language processing and demonstrates that neural network computing architecture can: (1) learn from actual spoken language; (2) observe rules of pronunciation; and (3) reproduce sounds from the patterns derived by its own processes. (Author/CB)

Development of Clinical Contents Model Markup Language for Electronic Health Records

PubMed Central

Yun, Ji-Hyun; Kim, Yoon

2012-01-01

Objectives To develop dedicated markup language for clinical contents models (CCM) to facilitate the active use of CCM in electronic health record systems. Methods Based on analysis of the structure and characteristics of CCM in the clinical domain, we designed extensible markup language (XML) based CCM markup language (CCML) schema manually. Results CCML faithfully reflects CCM in both the syntactic and semantic aspects. As this language is based on XML, it can be expressed and processed in computer systems and can be used in a technology-neutral way. Conclusions CCML has the following strengths: it is machine-readable and highly human-readable, it does not require a dedicated parser, and it can be applied for existing electronic health record systems. PMID:23115739

Learning for Semantic Parsing with Kernels under Various Forms of Supervision

DTIC Science & Technology

2007-08-01

natural language sentences to their formal executable meaning representations. This is a challenging problem and is critical for developing computing...sentences are semantically tractable. This indi- cates that Geoquery is more challenging domain for semantic parsing than ATIS. In the past, there have been a...Combining parsers. In Proceedings of the Conference on Em- pirical Methods in Natural Language Processing and Very Large Corpora (EMNLP/ VLC -99), pp. 187–194

Natural language information retrieval in digital libraries

DOE Office of Scientific and Technical Information (OSTI.GOV)

Strzalkowski, T.; Perez-Carballo, J.; Marinescu, M.

In this paper we report on some recent developments in joint NYU and GE natural language information retrieval system. The main characteristic of this system is the use of advanced natural language processing to enhance the effectiveness of term-based document retrieval. The system is designed around a traditional statistical backbone consisting of the indexer module, which builds inverted index files from pre-processed documents, and a retrieval engine which searches and ranks the documents in response to user queries. Natural language processing is used to (1) preprocess the documents in order to extract content-carrying terms, (2) discover inter-term dependencies and buildmore » a conceptual hierarchy specific to the database domain, and (3) process user`s natural language requests into effective search queries. This system has been used in NIST-sponsored Text Retrieval Conferences (TREC), where we worked with approximately 3.3 GBytes of text articles including material from the Wall Street Journal, the Associated Press newswire, the Federal Register, Ziff Communications`s Computer Library, Department of Energy abstracts, U.S. Patents and the San Jose Mercury News, totaling more than 500 million words of English. The system have been designed to facilitate its scalability to deal with ever increasing amounts of data. In particular, a randomized index-splitting mechanism has been installed which allows the system to create a number of smaller indexes that can be independently and efficiently searched.« less

Emerging Approach of Natural Language Processing in Opinion Mining: A Review

NASA Astrophysics Data System (ADS)

Kim, Tai-Hoon

Natural language processing (NLP) is a subfield of artificial intelligence and computational linguistics. It studies the problems of automated generation and understanding of natural human languages. This paper outlines a framework to use computer and natural language techniques for various levels of learners to learn foreign languages in Computer-based Learning environment. We propose some ideas for using the computer as a practical tool for learning foreign language where the most of courseware is generated automatically. We then describe how to build Computer Based Learning tools, discuss its effectiveness, and conclude with some possibilities using on-line resources.

State of the Art of Natural Language Processing

DTIC Science & Technology

1987-11-15

work of Chomsky , Hewlett-Packard, Generalized Phase Structure Grammar . D. Lunar, DARPA speech understanding, Schank’s Conceptual Dependency Theory...of computers that a machine which understood natural languages was highly desirable. It also was evident from the work of Chomsky * and others that...computers. ♦Noam Chomsky , Aspects of the Theory of Syntax (Cambridge, Mass.: MIT Press, 1965). -A- One of the earliest attempts at Natural Language

Developing Formal Correctness Properties from Natural Language Requirements

NASA Technical Reports Server (NTRS)

Nikora, Allen P.

2006-01-01

This viewgraph presentation reviews the rationale of the program to transform natural language specifications into formal notation.Specifically, automate generation of Linear Temporal Logic (LTL)correctness properties from natural language temporal specifications. There are several reasons for this approach (1) Model-based techniques becoming more widely accepted, (2) Analytical verification techniques (e.g., model checking, theorem proving) significantly more effective at detecting types of specification design errors (e.g., race conditions, deadlock) than manual inspection, (3) Many requirements still written in natural language, which results in a high learning curve for specification languages, associated tools and increased schedule and budget pressure on projects reduce training opportunities for engineers, and (4) Formulation of correctness properties for system models can be a difficult problem. This has relevance to NASA in that it would simplify development of formal correctness properties, lead to more widespread use of model-based specification, design techniques, assist in earlier identification of defects and reduce residual defect content for space mission software systems. The presentation also discusses: potential applications, accomplishments and/or technological transfer potential and the next steps.

Knowledge-Based Extensible Natural Language Interface Technology Program

DTIC Science & Technology

1989-11-30

natural language as its own meta-language to explain the meaning and attributes of the words and idioms of the larguage. Educational courses in language...understood and used by Lydia for human-computer dialogue. The KL enables a systems developer or " teacher -user" to build the system to a point where new...language can be "formal" as in a structured educational language program or it can be "informal" as in the case of a person consulting a dictionary for the

Natural Language Processing in Game Studies Research: An Overview

ERIC Educational Resources Information Center

Zagal, Jose P.; Tomuro, Noriko; Shepitsen, Andriy

2012-01-01

Natural language processing (NLP) is a field of computer science and linguistics devoted to creating computer systems that use human (natural) language as input and/or output. The authors propose that NLP can also be used for game studies research. In this article, the authors provide an overview of NLP and describe some research possibilities…

A Grammar-Based Semantic Similarity Algorithm for Natural Language Sentences

PubMed Central

Chang, Jia Wei; Hsieh, Tung Cheng

2014-01-01

This paper presents a grammar and semantic corpus based similarity algorithm for natural language sentences. Natural language, in opposition to “artificial language”, such as computer programming languages, is the language used by the general public for daily communication. Traditional information retrieval approaches, such as vector models, LSA, HAL, or even the ontology-based approaches that extend to include concept similarity comparison instead of cooccurrence terms/words, may not always determine the perfect matching while there is no obvious relation or concept overlap between two natural language sentences. This paper proposes a sentence similarity algorithm that takes advantage of corpus-based ontology and grammatical rules to overcome the addressed problems. Experiments on two famous benchmarks demonstrate that the proposed algorithm has a significant performance improvement in sentences/short-texts with arbitrary syntax and structure. PMID:24982952

Evolution, brain, and the nature of language.

PubMed

Berwick, Robert C; Friederici, Angela D; Chomsky, Noam; Bolhuis, Johan J

2013-02-01

Language serves as a cornerstone for human cognition, yet much about its evolution remains puzzling. Recent research on this question parallels Darwin's attempt to explain both the unity of all species and their diversity. What has emerged from this research is that the unified nature of human language arises from a shared, species-specific computational ability. This ability has identifiable correlates in the brain and has remained fixed since the origin of language approximately 100 thousand years ago. Although songbirds share with humans a vocal imitation learning ability, with a similar underlying neural organization, language is uniquely human. Copyright © 2012 Elsevier Ltd. All rights reserved.

Three Dimensions of Reproducibility in Natural Language Processing.

PubMed

Cohen, K Bretonnel; Xia, Jingbo; Zweigenbaum, Pierre; Callahan, Tiffany J; Hargraves, Orin; Goss, Foster; Ide, Nancy; Névéol, Aurélie; Grouin, Cyril; Hunter, Lawrence E

2018-05-01

Despite considerable recent attention to problems with reproducibility of scientific research, there is a striking lack of agreement about the definition of the term. That is a problem, because the lack of a consensus definition makes it difficult to compare studies of reproducibility, and thus to have even a broad overview of the state of the issue in natural language processing. This paper proposes an ontology of reproducibility in that field. Its goal is to enhance both future research and communication about the topic, and retrospective meta-analyses. We show that three dimensions of reproducibility, corresponding to three kinds of claims in natural language processing papers, can account for a variety of types of research reports. These dimensions are reproducibility of a conclusion , of a finding , and of a value. Three biomedical natural language processing papers by the authors of this paper are analyzed with respect to these dimensions.

A Natural Language Interface to Databases

NASA Technical Reports Server (NTRS)

Ford, D. R.

1990-01-01

The development of a Natural Language Interface (NLI) is presented which is semantic-based and uses Conceptual Dependency representation. The system was developed using Lisp and currently runs on a Symbolics Lisp machine.

Linear separability in superordinate natural language concepts.

PubMed

Ruts, Wim; Storms, Gert; Hampton, James

2004-01-01

Two experiments are reported in which linear separability was investigated in superordinate natural language concept pairs (e.g., toiletry-sewing gear). Representations of the exemplars of semantically related concept pairs were derived in two to five dimensions using multidimensional scaling (MDS) of similarities based on possession of the concept features. Next, category membership, obtained from an exemplar generation study (in Experiment 1) and from a forced-choice classification task (in Experiment 2) was predicted from the coordinates of the MDS representation using log linear analysis. The results showed that all natural kind concept pairs were perfectly linearly separable, whereas artifact concept pairs showed several violations. Clear linear separability of natural language concept pairs is in line with independent cue models. The violations in the artifact pairs, however, yield clear evidence against the independent cue models.

Ideas on Learning a New Language Intertwined with the Current State of Natural Language Processing and Computational Linguistics

ERIC Educational Resources Information Center

Snyder, Robin M.

2015-01-01

In 2014, in conjunction with doing research in natural language processing and attending a global conference on computational linguistics, the author decided to learn a new foreign language, Greek, that uses a non-English character set. This paper/session will present/discuss an overview of the current state of natural language processing and…

Multilingual natural language generation as part of a medical terminology server.

PubMed

Wagner, J C; Solomon, W D; Michel, P A; Juge, C; Baud, R H; Rector, A L; Scherrer, J R

1995-01-01

Re-usable and sharable, and therefore language-independent concept models are of increasing importance in the medical domain. The GALEN project (Generalized Architecture for Languages Encyclopedias and Nomenclatures in Medicine) aims at developing language-independent concept representation systems as the foundations for the next generation of multilingual coding systems. For use within clinical applications, the content of the model has to be mapped to natural language. A so-called Multilingual Information Module (MM) establishes the link between the language-independent concept model and different natural languages. This text generation software must be versatile enough to cope at the same time with different languages and with different parts of a compositional model. It has to meet, on the one hand, the properties of the language as used in the medical domain and, on the other hand, the specific characteristics of the underlying model and its representation formalism. We propose a semantic-oriented approach to natural language generation that is based on linguistic annotations to a concept model. This approach is realized as an integral part of a Terminology Server, built around the concept model and offering different terminological services for clinical applications.

ROPE: Recoverable Order-Preserving Embedding of Natural Language

DOE Office of Scientific and Technical Information (OSTI.GOV)

Widemann, David P.; Wang, Eric X.; Thiagarajan, Jayaraman J.

We present a novel Recoverable Order-Preserving Embedding (ROPE) of natural language. ROPE maps natural language passages from sparse concatenated one-hot representations to distributed vector representations of predetermined fixed length. We use Euclidean distance to return search results that are both grammatically and semantically similar. ROPE is based on a series of random projections of distributed word embeddings. We show that our technique typically forms a dictionary with sufficient incoherence such that sparse recovery of the original text is possible. We then show how our embedding allows for efficient and meaningful natural search and retrieval on Microsoft’s COCO dataset and themore » IMDB Movie Review dataset.« less

Towards Automatic Treatment of Natural Language.

ERIC Educational Resources Information Center

Lonsdale, Deryle

1984-01-01

Because automated natural language processing relies heavily on the still developing fields of linguistics, knowledge representation, and computational linguistics, no system is capable of mimicking human linguistic capabilities. For the present, interactive systems may be used to augment today's technology. (MSE)

Automated database design from natural language input

NASA Technical Reports Server (NTRS)

Gomez, Fernando; Segami, Carlos; Delaune, Carl

1995-01-01

Users and programmers of small systems typically do not have the skills needed to design a database schema from an English description of a problem. This paper describes a system that automatically designs databases for such small applications from English descriptions provided by end-users. Although the system has been motivated by the space applications at Kennedy Space Center, and portions of it have been designed with that idea in mind, it can be applied to different situations. The system consists of two major components: a natural language understander and a problem-solver. The paper describes briefly the knowledge representation structures constructed by the natural language understander, and, then, explains the problem-solver in detail.

The time course of syntactic activation during language processing: a model based on neuropsychological and neurophysiological data.

PubMed

Friederici, A D

1995-09-01

This paper presents a model describing the temporal and neurotopological structure of syntactic processes during comprehension. It postulates three distinct phases of language comprehension, two of which are primarily syntactic in nature. During the first phase the parser assigns the initial syntactic structure on the basis of word category information. These early structural processes are assumed to be subserved by the anterior parts of the left hemisphere, as event-related brain potentials show this area to be maximally activated when phrase structure violations are processed and as circumscribed lesions in this area lead to an impairment of the on-line structural assignment. During the second phase lexical-semantic and verb-argument structure information is processed. This phase is neurophysiologically manifest in a negative component in the event-related brain potential around 400 ms after stimulus onset which is distributed over the left and right temporo-parietal areas when lexical-semantic information is processed and over left anterior areas when verb-argument structure information is processed. During the third phase the parser tries to map the initial syntactic structure onto the available lexical-semantic and verb-argument structure information. In case of an unsuccessful match between the two types of information reanalyses may become necessary. These processes of structural reanalysis are correlated with a centroparietally distributed late positive component in the event-related brain potential.(ABSTRACT TRUNCATED AT 250 WORDS)

Semantics of Context-Free Fragments of Natural Languages.

ERIC Educational Resources Information Center

Suppes, Patrick

The objective of this paper is to combine the viewpoint of model-theoretic semantics and generative grammar, to define semantics for context-free languages, and to apply the results to some fragments of natural language. Following the introduction in the first section, Section 2 describes a simple artificial example to illustrate how a semantic…

Statistical Learning in a Natural Language by 8-Month-Old Infants

PubMed Central

Pelucchi, Bruna; Hay, Jessica F.; Saffran, Jenny R.

2013-01-01

Numerous studies over the past decade support the claim that infants are equipped with powerful statistical language learning mechanisms. The primary evidence for statistical language learning in word segmentation comes from studies using artificial languages, continuous streams of synthesized syllables that are highly simplified relative to real speech. To what extent can these conclusions be scaled up to natural language learning? In the current experiments, English-learning 8-month-old infants’ ability to track transitional probabilities in fluent infant-directed Italian speech was tested (N = 72). The results suggest that infants are sensitive to transitional probability cues in unfamiliar natural language stimuli, and support the claim that statistical learning is sufficiently robust to support aspects of real-world language acquisition. PMID:19489896

Statistical learning in a natural language by 8-month-old infants.

PubMed

Pelucchi, Bruna; Hay, Jessica F; Saffran, Jenny R

2009-01-01

Numerous studies over the past decade support the claim that infants are equipped with powerful statistical language learning mechanisms. The primary evidence for statistical language learning in word segmentation comes from studies using artificial languages, continuous streams of synthesized syllables that are highly simplified relative to real speech. To what extent can these conclusions be scaled up to natural language learning? In the current experiments, English-learning 8-month-old infants' ability to track transitional probabilities in fluent infant-directed Italian speech was tested (N = 72). The results suggest that infants are sensitive to transitional probability cues in unfamiliar natural language stimuli, and support the claim that statistical learning is sufficiently robust to support aspects of real-world language acquisition.

Learning to Understand Natural Language with Less Human Effort

DTIC Science & Technology

2015-05-01

j ); if one of these has the correct logical form, ` j = `i, then tj is taken as the approximate maximizer. 29 2.3 Discussion This chapter...where j indexes entity tuples (e1, e2). Training optimizes the semantic parser parameters θ to predict Y = yj,Z = zj given S = sj . The parameters θ...be au tif ul / J J N 1 /N 1 λ f .f L on do n /N N P N λ x .M (x ,“ lo nd on ”, C IT Y ) N : λ x .M (x ,“ lo nd on ”, C IT Y ) (S [d cl ]\\N

Parent-Implemented Natural Language Paradigm to Increase Language and Play in Children with Autism

ERIC Educational Resources Information Center

Gillett, Jill N.; LeBlanc, Linda A.

2007-01-01

Three parents of children with autism were taught to implement the Natural Language Paradigm (NLP). Data were collected on parent implementation, multiple measures of child language, and play. The parents were able to learn to implement the NLP procedures quickly and accurately with beneficial results for their children. Increases in the overall…

Evaluation of Natural Language Processors.

DTIC Science & Technology

1980-11-01

techniques described. Common practice in describing natural language processors is to describe the programs, then give about 20 examples of correctly...make a decision based on performance as to which approaches are most promising for further research and development. The lack of evaluation leaves...successively more difficult problems. This approach might be compared to children taking achievement tests in school. A 90% score on problems involving

A Portable Natural Language Interface.

DTIC Science & Technology

1987-09-01

regrets. - 27 - BIBLIOGRAPHY Bayer, Samuel. "A Theory of Linearization in Relational Grammar ," Senior essay, Yale University , 1984. Dyer, Michael. In... Grammar 1. Chicago: University Chicago Press, 1983. Rustin, R., ed., Natural Language Processing. New York: Algorithmics Press, 1973. Wasow, Tom...most notably, the theory of relational grammar developed by Perlmutter and his associates, and the theory of discourse developed by Barbara Grosz

Neurolinguistics and psycholinguistics as a basis for computer acquisition of natural language

DOE Office of Scientific and Technical Information (OSTI.GOV)

Powers, D.M.W.

1983-04-01

Research into natural language understanding systems for computers has concentrated on implementing particular grammars and grammatical models of the language concerned. This paper presents a rationale for research into natural language understanding systems based on neurological and psychological principles. Important features of the approach are that it seeks to place the onus of learning the language on the computer, and that it seeks to make use of the vast wealth of relevant psycholinguistic and neurolinguistic theory. 22 references.

Integrating a Natural Language Message Pre-Processor with UIMA

DTIC Science & Technology

2008-01-01

Carnegie Mellon Language Technologies Institute NL Message Preprocessing with UIMA Copyright © 2008, Carnegie Mellon. All Rights Reserved...Integrating a Natural Language Message Pre-Processor with UIMA Eric Nyberg, Eric Riebling, Richard C. Wang & Robert Frederking Language Technologies Institute...with UIMA 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER

Robo-Sensei's NLP-Based Error Detection and Feedback Generation

ERIC Educational Resources Information Center

Nagata, Noriko

2009-01-01

This paper presents a new version of Robo-Sensei's NLP (Natural Language Processing) system which updates the version currently available as the software package "ROBO-SENSEI: Personal Japanese Tutor" (Nagata, 2004). Robo-Sensei's NLP system includes a lexicon, a morphological generator, a word segmentor, a morphological parser, a syntactic…

Human-Level Natural Language Understanding: False Progress and Real Challenges

ERIC Educational Resources Information Center

Bignoli, Perrin G.

2013-01-01

The field of Natural Language Processing (NLP) focuses on the study of how utterances composed of human-level languages can be understood and generated. Typically, there are considered to be three intertwined levels of structure that interact to create meaning in language: syntax, semantics, and pragmatics. Not only is a large amount of…

Deciphering the language of nature: cryptography, secrecy, and alterity in Francis Bacon.

PubMed

Clody, Michael C

2011-01-01

The essay argues that Francis Bacon's considerations of parables and cryptography reflect larger interpretative concerns of his natural philosophic project. Bacon describes nature as having a language distinct from those of God and man, and, in so doing, establishes a central problem of his natural philosophy—namely, how can the language of nature be accessed through scientific representation? Ultimately, Bacon's solution relies on a theory of differential and duplicitous signs that conceal within them the hidden voice of nature, which is best recognized in the natural forms of efficient causality. The "alphabet of nature"—those tables of natural occurrences—consequently plays a central role in his program, as it renders nature's language susceptible to a process and decryption that mirrors the model of the bilateral cipher. It is argued that while the writing of Bacon's natural philosophy strives for literality, its investigative process preserves a space for alterity within scientific representation, that is made accessible to those with the interpretative key.

Getting Answers to Natural Language Questions on the Web.

ERIC Educational Resources Information Center

Radev, Dragomir R.; Libner, Kelsey; Fan, Weiguo

2002-01-01

Describes a study that investigated the use of natural language questions on Web search engines. Highlights include query languages; differences in search engine syntax; and results of logistic regression and analysis of variance that showed aspects of questions that predicted significantly different performances, including the number of words,…

Two Interpretive Systems for Natural Language?

ERIC Educational Resources Information Center

Frazier, Lyn

2015-01-01

It is proposed that humans have available to them two systems for interpreting natural language. One system is familiar from formal semantics. It is a type based system that pairs a syntactic form with its interpretation using grammatical rules of composition. This system delivers both plausible and implausible meanings. The other proposed system…

Learning procedures from interactive natural language instructions

NASA Technical Reports Server (NTRS)

Huffman, Scott B.; Laird, John E.

1994-01-01

Despite its ubiquity in human learning, very little work has been done in artificial intelligence on agents that learn from interactive natural language instructions. In this paper, the problem of learning procedures from interactive, situated instruction is examined in which the student is attempting to perform tasks within the instructional domain, and asks for instruction when it is needed. Presented is Instructo-Soar, a system that behaves and learns in response to interactive natural language instructions. Instructo-Soar learns completely new procedures from sequences of instruction, and also learns how to extend its knowledge of previously known procedures to new situations. These learning tasks require both inductive and analytic learning. Instructo-Soar exhibits a multiple execution learning process in which initial learning has a rote, episodic flavor, and later executions allow the initially learned knowledge to be generalized properly.

The power and limits of a rule-based morpho-semantic parser.

PubMed Central

Baud, R. H.; Rassinoux, A. M.; Ruch, P.; Lovis, C.; Scherrer, J. R.

1999-01-01

The venue of Electronic Patient Record (EPR) implies an increasing amount of medical texts readily available for processing, as soon as convenient tools are made available. The chief application is text analysis, from which one can drive other disciplines like indexing for retrieval, knowledge representation, translation and inferencing for medical intelligent systems. Prerequisites for a convenient analyzer of medical texts are: building the lexicon, developing semantic representation of the domain, having a large corpus of texts available for statistical analysis, and finally mastering robust and powerful parsing techniques in order to satisfy the constraints of the medical domain. This article aims at presenting an easy-to-use parser ready to be adapted in different settings. It describes its power together with its practical limitations as experienced by the authors. PMID:10566313

The power and limits of a rule-based morpho-semantic parser.

PubMed

Baud, R H; Rassinoux, A M; Ruch, P; Lovis, C; Scherrer, J R

1999-01-01

The venue of Electronic Patient Record (EPR) implies an increasing amount of medical texts readily available for processing, as soon as convenient tools are made available. The chief application is text analysis, from which one can drive other disciplines like indexing for retrieval, knowledge representation, translation and inferencing for medical intelligent systems. Prerequisites for a convenient analyzer of medical texts are: building the lexicon, developing semantic representation of the domain, having a large corpus of texts available for statistical analysis, and finally mastering robust and powerful parsing techniques in order to satisfy the constraints of the medical domain. This article aims at presenting an easy-to-use parser ready to be adapted in different settings. It describes its power together with its practical limitations as experienced by the authors.

Dependency distance: A new perspective on syntactic patterns in natural languages

NASA Astrophysics Data System (ADS)

Liu, Haitao; Xu, Chunshan; Liang, Junying

2017-07-01

Dependency distance, measured by the linear distance between two syntactically related words in a sentence, is generally held as an important index of memory burden and an indicator of syntactic difficulty. Since this constraint of memory is common for all human beings, there may well be a universal preference for dependency distance minimization (DDM) for the sake of reducing memory burden. This human-driven language universal is supported by big data analyses of various corpora that consistently report shorter overall dependency distance in natural languages than in artificial random languages and long-tailed distributions featuring a majority of short dependencies and a minority of long ones. Human languages, as complex systems, seem to have evolved to come up with diverse syntactic patterns under the universal pressure for dependency distance minimization. However, there always exist a small number of long-distance dependencies in natural languages, which may reflect some other biological or functional constraints. Language system may adapt itself to these sporadic long-distance dependencies. It is these universal constraints that have shaped such a rich diversity of syntactic patterns in human languages.

The language of nature matters: we need a more public ecology

Treesearch

Bruce R. Hull; David P. Robertson

2000-01-01

The language we use to describe nature matters. It is used by policy analysts to set goals for ecological restoration and management, by scientists to describe the nature that did, does, or could exist, and by all of us to imagine possible and acceptable conditions of environmental quality. Participants in environmental decision making demand a lot of the language and...

The CMS DBS query language

NASA Astrophysics Data System (ADS)

Kuznetsov, Valentin; Riley, Daniel; Afaq, Anzar; Sekhri, Vijay; Guo, Yuyi; Lueking, Lee

2010-04-01

The CMS experiment has implemented a flexible and powerful system enabling users to find data within the CMS physics data catalog. The Dataset Bookkeeping Service (DBS) comprises a database and the services used to store and access metadata related to CMS physics data. To this, we have added a generalized query system in addition to the existing web and programmatic interfaces to the DBS. This query system is based on a query language that hides the complexity of the underlying database structure by discovering the join conditions between database tables. This provides a way of querying the system that is simple and straightforward for CMS data managers and physicists to use without requiring knowledge of the database tables or keys. The DBS Query Language uses the ANTLR tool to build the input query parser and tokenizer, followed by a query builder that uses a graph representation of the DBS schema to construct the SQL query sent to underlying database. We will describe the design of the query system, provide details of the language components and overview of how this component fits into the overall data discovery system architecture.

A natural language interface plug-in for cooperative query answering in biological databases.

PubMed

Jamil, Hasan M

2012-06-11

One of the many unique features of biological databases is that the mere existence of a ground data item is not always a precondition for a query response. It may be argued that from a biologist's standpoint, queries are not always best posed using a structured language. By this we mean that approximate and flexible responses to natural language like queries are well suited for this domain. This is partly due to biologists' tendency to seek simpler interfaces and partly due to the fact that questions in biology involve high level concepts that are open to interpretations computed using sophisticated tools. In such highly interpretive environments, rigidly structured databases do not always perform well. In this paper, our goal is to propose a semantic correspondence plug-in to aid natural language query processing over arbitrary biological database schema with an aim to providing cooperative responses to queries tailored to users' interpretations. Natural language interfaces for databases are generally effective when they are tuned to the underlying database schema and its semantics. Therefore, changes in database schema become impossible to support, or a substantial reorganization cost must be absorbed to reflect any change. We leverage developments in natural language parsing, rule languages and ontologies, and data integration technologies to assemble a prototype query processor that is able to transform a natural language query into a semantically equivalent structured query over the database. We allow knowledge rules and their frequent modifications as part of the underlying database schema. The approach we adopt in our plug-in overcomes some of the serious limitations of many contemporary natural language interfaces, including support for schema modifications and independence from underlying database schema. The plug-in introduced in this paper is generic and facilitates connecting user selected natural language interfaces to arbitrary databases using a

Unsupervised learning of natural languages

PubMed Central

Solan, Zach; Horn, David; Ruppin, Eytan; Edelman, Shimon

2005-01-01

We address the problem, fundamental to linguistics, bioinformatics, and certain other disciplines, of using corpora of raw symbolic sequential data to infer underlying rules that govern their production. Given a corpus of strings (such as text, transcribed speech, chromosome or protein sequence data, sheet music, etc.), our unsupervised algorithm recursively distills from it hierarchically structured patterns. The adios (automatic distillation of structure) algorithm relies on a statistical method for pattern extraction and on structured generalization, two processes that have been implicated in language acquisition. It has been evaluated on artificial context-free grammars with thousands of rules, on natural languages as diverse as English and Chinese, and on protein data correlating sequence with function. This unsupervised algorithm is capable of learning complex syntax, generating grammatical novel sentences, and proving useful in other fields that call for structure discovery from raw data, such as bioinformatics. PMID:16087885

Unsupervised learning of natural languages.

PubMed

Solan, Zach; Horn, David; Ruppin, Eytan; Edelman, Shimon

2005-08-16

We address the problem, fundamental to linguistics, bioinformatics, and certain other disciplines, of using corpora of raw symbolic sequential data to infer underlying rules that govern their production. Given a corpus of strings (such as text, transcribed speech, chromosome or protein sequence data, sheet music, etc.), our unsupervised algorithm recursively distills from it hierarchically structured patterns. The adios (automatic distillation of structure) algorithm relies on a statistical method for pattern extraction and on structured generalization, two processes that have been implicated in language acquisition. It has been evaluated on artificial context-free grammars with thousands of rules, on natural languages as diverse as English and Chinese, and on protein data correlating sequence with function. This unsupervised algorithm is capable of learning complex syntax, generating grammatical novel sentences, and proving useful in other fields that call for structure discovery from raw data, such as bioinformatics.

Automatic Item Generation via Frame Semantics: Natural Language Generation of Math Word Problems.

ERIC Educational Resources Information Center

Deane, Paul; Sheehan, Kathleen

This paper is an exploration of the conceptual issues that have arisen in the course of building a natural language generation (NLG) system for automatic test item generation. While natural language processing techniques are applicable to general verbal items, mathematics word problems are particularly tractable targets for natural language…

Natural language generation in health care.

PubMed

Cawsey, A J; Webber, B L; Jones, R B

1997-01-01

Good communication is vital in health care, both among health care professionals, and between health care professionals and their patients. And well-written documents, describing and/or explaining the information in structured databases may be easier to comprehend, more edifying, and even more convincing than the structured data, even when presented in tabular or graphic form. Documents may be automatically generated from structured data, using techniques from the field of natural language generation. These techniques are concerned with how the content, organization and language used in a document can be dynamically selected, depending on the audience and context. They have been used to generate health education materials, explanations and critiques in decision support systems, and medical reports and progress notes.

Anaphora and Logical Form: On Formal Meaning Representations for Natural Language. Technical Report No. 36.

ERIC Educational Resources Information Center

Nash-Webber, Bonnie; Reiter, Raymond

This paper describes a computational approach to certain problems of anaphora in natural language and argues in favor of formal meaning representation languages (MRLs) for natural language. After presenting arguments in favor of formal meaning representation languages, appropriate MRLs are discussed. Minimal requirements include provisions for…

Natural language processing and the Now-or-Never bottleneck.

PubMed

Gómez-Rodríguez, Carlos

2016-01-01

Researchers, motivated by the need to improve the efficiency of natural language processing tools to handle web-scale data, have recently arrived at models that remarkably match the expected features of human language processing under the Now-or-Never bottleneck framework. This provides additional support for said framework and highlights the research potential in the interaction between applied computational linguistics and cognitive science.

A Codasyl-Type Schema for Natural Language Medical Records

PubMed Central

Sager, N.; Tick, L.; Story, G.; Hirschman, L.

1980-01-01

This paper describes a CODASYL (network) database schema for information derived from narrative clinical reports. The goal of this work is to create an automated process that accepts natural language documents as input and maps this information into a database of a type managed by existing database management systems. The schema described here represents the medical events and facts identified through the natural language processing. This processing decomposes each narrative into a set of elementary assertions, represented as MEDFACT records in the database. Each assertion in turn consists of a subject and a predicate classed according to a limited number of medical event types, e.g., signs/symptoms, laboratory tests, etc. The subject and predicate are represented by EVENT records which are owned by the MEDFACT record associated with the assertion. The CODASYL-type network structure was found to be suitable for expressing most of the relations needed to represent the natural language information. However, special mechanisms were developed for storing the time relations between EVENT records and for recording connections (such as causality) between certain MEDFACT records. This schema has been implemented using the UNIVAC DMS-1100 DBMS.

Dependency distances in natural mixed languages. Comment on "Dependency distance: A new perspective on syntactic patterns in natural languages" by Haitao Liu et al.

NASA Astrophysics Data System (ADS)

Wang, Lin

2017-07-01

Haitao Liu et al.'s article [1] offers a comprehensive account of the diversity of syntactic patterns in human languages in terms of an important index of memory burden and syntactic difficulty - the dependency distance. Natural languages, a complex system, present overall shorter dependency distances under the universal pressure for dependency distance minimization; however, there exist some relatively-long-distance dependencies, which reflect that language can constantly adapt itself to some deep-level biological or functional constraints.

Dependency distance: A new perspective on syntactic patterns in natural languages.

PubMed

Liu, Haitao; Xu, Chunshan; Liang, Junying

2017-07-01

Dependency distance, measured by the linear distance between two syntactically related words in a sentence, is generally held as an important index of memory burden and an indicator of syntactic difficulty. Since this constraint of memory is common for all human beings, there may well be a universal preference for dependency distance minimization (DDM) for the sake of reducing memory burden. This human-driven language universal is supported by big data analyses of various corpora that consistently report shorter overall dependency distance in natural languages than in artificial random languages and long-tailed distributions featuring a majority of short dependencies and a minority of long ones. Human languages, as complex systems, seem to have evolved to come up with diverse syntactic patterns under the universal pressure for dependency distance minimization. However, there always exist a small number of long-distance dependencies in natural languages, which may reflect some other biological or functional constraints. Language system may adapt itself to these sporadic long-distance dependencies. It is these universal constraints that have shaped such a rich diversity of syntactic patterns in human languages. Copyright © 2017. Published by Elsevier B.V.

Conclusiveness of natural languages and recognition of images

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wojcik, Z.M.

1983-01-01

The conclusiveness is investigated using recognition processes and one-one correspondence between expressions of a natural language and graphs representing events. The graphs, as conceived in psycholinguistics, are obtained as a result of perception processes. It is possible to generate and process the graphs automatically, using computers and then to convert the resulting graphs into expressions of a natural language. Correctness and conclusiveness of the graphs and sentences are investigated using the fundamental condition for events representation processes. Some consequences of the conclusiveness are discussed, e.g. undecidability of arithmetic, human brain assymetry, correctness of statistical calculations and operations research. It ismore » suggested that the group theory should be imposed on mathematical models of any real system. Proof of the fundamental condition is also presented. 14 references.« less

Selecting the Best Mobile Information Service with Natural Language User Input

NASA Astrophysics Data System (ADS)

Feng, Qiangze; Qi, Hongwei; Fukushima, Toshikazu

Information services accessed via mobile phones provide information directly relevant to subscribers’ daily lives and are an area of dynamic market growth worldwide. Although many information services are currently offered by mobile operators, many of the existing solutions require a unique gateway for each service, and it is inconvenient for users to have to remember a large number of such gateways. Furthermore, the Short Message Service (SMS) is very popular in China and Chinese users would prefer to access these services in natural language via SMS. This chapter describes a Natural Language Based Service Selection System (NL3S) for use with a large number of mobile information services. The system can accept user queries in natural language and navigate it to the required service. Since it is difficult for existing methods to achieve high accuracy and high coverage and anticipate which other services a user might want to query, the NL3S is developed based on a Multi-service Ontology (MO) and Multi-service Query Language (MQL). The MO and MQL provide semantic and linguistic knowledge, respectively, to facilitate service selection for a user query and to provide adaptive service recommendations. Experiments show that the NL3S can achieve 75-95% accuracies and 85-95% satisfactions for processing various styles of natural language queries. A trial involving navigation of 30 different mobile services shows that the NL3S can provide a viable commercial solution for mobile operators.

QATT: a Natural Language Interface for QPE. M.S. Thesis

NASA Technical Reports Server (NTRS)

White, Douglas Robert-Graham

1989-01-01

QATT, a natural language interface developed for the Qualitative Process Engine (QPE) system is presented. The major goal was to evaluate the use of a preexisting natural language understanding system designed to be tailored for query processing in multiple domains of application. The other goal of QATT is to provide a comfortable environment in which to query envisionments in order to gain insight into the qualitative behavior of physical systems. It is shown that the use of the preexisting system made possible the development of a reasonably useful interface in a few months.

Three-dimensional grammar in the brain: Dissociating the neural correlates of natural sign language and manually coded spoken language.

PubMed

Jednoróg, Katarzyna; Bola, Łukasz; Mostowski, Piotr; Szwed, Marcin; Boguszewski, Paweł M; Marchewka, Artur; Rutkowski, Paweł

2015-05-01

In several countries natural sign languages were considered inadequate for education. Instead, new sign-supported systems were created, based on the belief that spoken/written language is grammatically superior. One such system called SJM (system językowo-migowy) preserves the grammatical and lexical structure of spoken Polish and since 1960s has been extensively employed in schools and on TV. Nevertheless, the Deaf community avoids using SJM for everyday communication, its preferred language being PJM (polski język migowy), a natural sign language, structurally and grammatically independent of spoken Polish and featuring classifier constructions (CCs). Here, for the first time, we compare, with fMRI method, the neural bases of natural vs. devised communication systems. Deaf signers were presented with three types of signed sentences (SJM and PJM with/without CCs). Consistent with previous findings, PJM with CCs compared to either SJM or PJM without CCs recruited the parietal lobes. The reverse comparison revealed activation in the anterior temporal lobes, suggesting increased semantic combinatory processes in lexical sign comprehension. Finally, PJM compared with SJM engaged left posterior superior temporal gyrus and anterior temporal lobe, areas crucial for sentence-level speech comprehension. We suggest that activity in these two areas reflects greater processing efficiency for naturally evolved sign language. Copyright © 2015 Elsevier Ltd. All rights reserved.

A Look at Natural Language Retrieval Systems

ERIC Educational Resources Information Center

Townley, Helen M.

1971-01-01

Natural language systems are seen as falling into two classes - those which process and analyse the input and store it in an ordered fashion, and those which employ controls at the output stage. A variety of systems of both types is reviewed, and their respective features are discussed. (12 references) (Author/NH)

Incremental Bayesian Category Learning from Natural Language

ERIC Educational Resources Information Center

Frermann, Lea; Lapata, Mirella

2016-01-01

Models of category learning have been extensively studied in cognitive science and primarily tested on perceptual abstractions or artificial stimuli. In this paper, we focus on categories acquired from natural language stimuli, that is, words (e.g., "chair" is a member of the furniture category). We present a Bayesian model that, unlike…

Interactive natural language acquisition in a multi-modal recurrent neural architecture

NASA Astrophysics Data System (ADS)

Heinrich, Stefan; Wermter, Stefan

2018-01-01

For the complex human brain that enables us to communicate in natural language, we gathered good understandings of principles underlying language acquisition and processing, knowledge about sociocultural conditions, and insights into activity patterns in the brain. However, we were not yet able to understand the behavioural and mechanistic characteristics for natural language and how mechanisms in the brain allow to acquire and process language. In bridging the insights from behavioural psychology and neuroscience, the goal of this paper is to contribute a computational understanding of appropriate characteristics that favour language acquisition. Accordingly, we provide concepts and refinements in cognitive modelling regarding principles and mechanisms in the brain and propose a neurocognitively plausible model for embodied language acquisition from real-world interaction of a humanoid robot with its environment. In particular, the architecture consists of a continuous time recurrent neural network, where parts have different leakage characteristics and thus operate on multiple timescales for every modality and the association of the higher level nodes of all modalities into cell assemblies. The model is capable of learning language production grounded in both, temporal dynamic somatosensation and vision, and features hierarchical concept abstraction, concept decomposition, multi-modal integration, and self-organisation of latent representations.

Testing of a Natural Language Retrieval System for a Full Text Knowledge Base.

ERIC Educational Resources Information Center

Bernstein, Lionel M.; Williamson, Robert E.

1984-01-01

The Hepatitis Knowledge Base (text of prototype information system) was used for modifying and testing "A Navigator of Natural Language Organized (Textual) Data" (ANNOD), a retrieval system which combines probabilistic, linguistic, and empirical means to rank individual paragraphs of full text for similarity to natural language queries…

Natural language processing and advanced information management

NASA Technical Reports Server (NTRS)

Hoard, James E.

1989-01-01

Integrating diverse information sources and application software in a principled and general manner will require a very capable advanced information management (AIM) system. In particular, such a system will need a comprehensive addressing scheme to locate the material in its docuverse. It will also need a natural language processing (NLP) system of great sophistication. It seems that the NLP system must serve three functions. First, it provides an natural language interface (NLI) for the users. Second, it serves as the core component that understands and makes use of the real-world interpretations (RWIs) contained in the docuverse. Third, it enables the reasoning specialists (RSs) to arrive at conclusions that can be transformed into procedures that will satisfy the users' requests. The best candidate for an intelligent agent that can satisfactorily make use of RSs and transform documents (TDs) appears to be an object oriented data base (OODB). OODBs have, apparently, an inherent capacity to use the large numbers of RSs and TDs that will be required by an AIM system and an inherent capacity to use them in an effective way.

ChemicalTagger: A tool for semantic text-mining in chemistry

PubMed Central

2011-01-01

Background The primary method for scientific communication is in the form of published scientific articles and theses which use natural language combined with domain-specific terminology. As such, they contain free owing unstructured text. Given the usefulness of data extraction from unstructured literature, we aim to show how this can be achieved for the discipline of chemistry. The highly formulaic style of writing most chemists adopt make their contributions well suited to high-throughput Natural Language Processing (NLP) approaches. Results We have developed the ChemicalTagger parser as a medium-depth, phrase-based semantic NLP tool for the language of chemical experiments. Tagging is based on a modular architecture and uses a combination of OSCAR, domain-specific regex and English taggers to identify parts-of-speech. The ANTLR grammar is used to structure this into tree-based phrases. Using a metric that allows for overlapping annotations, we achieved machine-annotator agreements of 88.9% for phrase recognition and 91.9% for phrase-type identification (Action names). Conclusions It is possible parse to chemical experimental text using rule-based techniques in conjunction with a formal grammar parser. ChemicalTagger has been deployed for over 10,000 patents and has identified solvents from their linguistic context with >99.5% precision. PMID:21575201

ChemicalTagger: A tool for semantic text-mining in chemistry.

PubMed

Hawizy, Lezan; Jessop, David M; Adams, Nico; Murray-Rust, Peter

2011-05-16

The primary method for scientific communication is in the form of published scientific articles and theses which use natural language combined with domain-specific terminology. As such, they contain free owing unstructured text. Given the usefulness of data extraction from unstructured literature, we aim to show how this can be achieved for the discipline of chemistry. The highly formulaic style of writing most chemists adopt make their contributions well suited to high-throughput Natural Language Processing (NLP) approaches. We have developed the ChemicalTagger parser as a medium-depth, phrase-based semantic NLP tool for the language of chemical experiments. Tagging is based on a modular architecture and uses a combination of OSCAR, domain-specific regex and English taggers to identify parts-of-speech. The ANTLR grammar is used to structure this into tree-based phrases. Using a metric that allows for overlapping annotations, we achieved machine-annotator agreements of 88.9% for phrase recognition and 91.9% for phrase-type identification (Action names). It is possible parse to chemical experimental text using rule-based techniques in conjunction with a formal grammar parser. ChemicalTagger has been deployed for over 10,000 patents and has identified solvents from their linguistic context with >99.5% precision.

Structured Natural-Language Descriptions for Semantic Content Retrieval of Visual Materials.

ERIC Educational Resources Information Center

Tam, A. M.; Leung, C. H. C.

2001-01-01

Proposes a structure for natural language descriptions of the semantic content of visual materials that requires descriptions to be (modified) keywords, phrases, or simple sentences, with components that are grammatical relations common to many languages. This structure makes it easy to implement a collection's descriptions as a relational…

Sorry Dave, I’m Afraid I Can’t Do That: Explaining Unachievable Robot Tasks using Natural Language

DTIC Science & Technology

2013-06-24

processing components used by Brooks et al. [6]: the Bikel parser [3] combined with the null element (understood subject) restoration of Gabbard et al...Intelligent Robots and Systems (IROS), pages 1988 – 1993, 2010. [12] Ryan Gabbard , Mitch Marcus, and Seth Kulick. Fully parsing the Penn Treebank. In Human

Dynamic changes in network activations characterize early learning of a natural language.

PubMed

Plante, Elena; Patterson, Dianne; Dailey, Natalie S; Kyle, R Almyrde; Fridriksson, Julius

2014-09-01

Those who are initially exposed to an unfamiliar language have difficulty separating running speech into individual words, but over time will recognize both words and the grammatical structure of the language. Behavioral studies have used artificial languages to demonstrate that humans are sensitive to distributional information in language input, and can use this information to discover the structure of that language. This is done without direct instruction and learning occurs over the course of minutes rather than days or months. Moreover, learners may attend to different aspects of the language input as their own learning progresses. Here, we examine processing associated with the early stages of exposure to a natural language, using fMRI. Listeners were exposed to an unfamiliar language (Icelandic) while undergoing four consecutive fMRI scans. The Icelandic stimuli were constrained in ways known to produce rapid learning of aspects of language structure. After approximately 4 min of exposure to the Icelandic stimuli, participants began to differentiate between correct and incorrect sentences at above chance levels, with significant improvement between the first and last scan. An independent component analysis of the imaging data revealed four task-related components, two of which were associated with behavioral performance early in the experiment, and two with performance later in the experiment. This outcome suggests dynamic changes occur in the recruitment of neural resources even within the initial period of exposure to an unfamiliar natural language. Copyright © 2014 Elsevier Ltd. All rights reserved.

Semantic biomedical resource discovery: a Natural Language Processing framework.

PubMed

Sfakianaki, Pepi; Koumakis, Lefteris; Sfakianakis, Stelios; Iatraki, Galatia; Zacharioudakis, Giorgos; Graf, Norbert; Marias, Kostas; Tsiknakis, Manolis

2015-09-30

A plethora of publicly available biomedical resources do currently exist and are constantly increasing at a fast rate. In parallel, specialized repositories are been developed, indexing numerous clinical and biomedical tools. The main drawback of such repositories is the difficulty in locating appropriate resources for a clinical or biomedical decision task, especially for non-Information Technology expert users. In parallel, although NLP research in the clinical domain has been active since the 1960s, progress in the development of NLP applications has been slow and lags behind progress in the general NLP domain. The aim of the present study is to investigate the use of semantics for biomedical resources annotation with domain specific ontologies and exploit Natural Language Processing methods in empowering the non-Information Technology expert users to efficiently search for biomedical resources using natural language. A Natural Language Processing engine which can "translate" free text into targeted queries, automatically transforming a clinical research question into a request description that contains only terms of ontologies, has been implemented. The implementation is based on information extraction techniques for text in natural language, guided by integrated ontologies. Furthermore, knowledge from robust text mining methods has been incorporated to map descriptions into suitable domain ontologies in order to ensure that the biomedical resources descriptions are domain oriented and enhance the accuracy of services discovery. The framework is freely available as a web application at ( http://calchas.ics.forth.gr/ ). For our experiments, a range of clinical questions were established based on descriptions of clinical trials from the ClinicalTrials.gov registry as well as recommendations from clinicians. Domain experts manually identified the available tools in a tools repository which are suitable for addressing the clinical questions at hand, either

Semantic Grammar: An Engineering Technique for Constructing Natural Language Understanding Systems.

ERIC Educational Resources Information Center

Burton, Richard R.

In an attempt to overcome the lack of natural means of communication between student and computer, this thesis addresses the problem of developing a system which can understand natural language within an educational problem-solving environment. The nature of the environment imposes efficiency, habitability, self-teachability, and awareness of…

Blurring the Inputs: A Natural Language Approach to Sensitivity Analysis

NASA Technical Reports Server (NTRS)

Kleb, William L.; Thompson, Richard A.; Johnston, Christopher O.

2007-01-01

To document model parameter uncertainties and to automate sensitivity analyses for numerical simulation codes, a natural-language-based method to specify tolerances has been developed. With this new method, uncertainties are expressed in a natural manner, i.e., as one would on an engineering drawing, namely, 5.25 +/- 0.01. This approach is robust and readily adapted to various application domains because it does not rely on parsing the particular structure of input file formats. Instead, tolerances of a standard format are added to existing fields within an input file. As a demonstration of the power of this simple, natural language approach, a Monte Carlo sensitivity analysis is performed for three disparate simulation codes: fluid dynamics (LAURA), radiation (HARA), and ablation (FIAT). Effort required to harness each code for sensitivity analysis was recorded to demonstrate the generality and flexibility of this new approach.

Design of Lexicons in Some Natural Language Systems.

ERIC Educational Resources Information Center

Cercone, Nick; Mercer, Robert

1980-01-01

Discusses an investigation of certain problems concerning the structural design of lexicons used in computational approaches to natural language understanding. Emphasizes three aspects of design: retrieval of relevant portions of lexicals items, storage requirements, and representation of meaning in the lexicon. (Available from ALLC, Dr. Rex Last,…

Role of PROLOG (Programming and Logic) in natural-language processing. Report for September-December 1987

DOE Office of Scientific and Technical Information (OSTI.GOV)

McHale, M.L.

The field of artificial Intelligence strives to produce computer programs that exhibit intelligent behavior. One of the areas of interest is the processing of natural language. This report discusses the role of the computer language PROLOG in Natural Language Processing (NLP) both from theoretic and pragmatic viewpoints. The reasons for using PROLOG for NLP are numerous. First, linguists can write natural-language grammars almost directly as PROLOG programs; this allows fast-prototyping of NLP systems and facilitates analysis of NLP theories. Second, semantic representations of natural-language texts that use logic formalisms are readily produced in PROLOG because of PROLOG's logical foundations. Third,more » PROLOG's built-in inferencing mechanisms are often sufficient for inferences on the logical forms produced by NLPs. Fourth, the logical, declarative nature of PROLOG may make it the language of choice for parallel computing systems. Finally, the fact that PROLOG has a de facto standard (Edinburgh) makes the porting of code from one computer system to another virtually trouble free. Perhaps the strongest tie one could make between NLP and PROLOG was stated by John Stuart Mill in his inaugural Address at St. Andrews: The structure of every sentence is a lesson in logic.« less

Understanding and representing natural language meaning

NASA Astrophysics Data System (ADS)

Waltz, D. L.; Maran, L. R.; Dorfman, M. H.; Dinitz, R.; Farwell, D.

1982-12-01

During this contract period the authors have: (1) continued investigation of events and actions by means of representation schemes called 'event shape diagrams'; (2) written a parsing program which selects appropriate word and sentence meanings by a parallel process know as activation and inhibition; (3) begun investigation of the point of a story or event by modeling the motivations and emotional behaviors of story characters; (4) started work on combining and translating two machine-readable dictionaries into a lexicon and knowledge base which will form an integral part of our natural language understanding programs; (5) made substantial progress toward a general model for the representation of cognitive relations by comparing English scene and event descriptions with similar descriptions in other languages; (6) constructed a general model for the representation of tense and aspect of verbs; (7) made progress toward the design of an integrated robotics system which accepts English requests, and uses visual and tactile inputs in making decisions and learning new tasks.

The State-of-the-Art in Natural Language Understanding.

DTIC Science & Technology

1981-01-28

driven text analysis. If we know a story is about a restaurant, we expect that we may encounter a waitress, menu, table, a bill, food , and other... Pront aids for Data Bases During the 70’s a number of natural language data base front ends apreared: LUNPLR Woods et al 19721 has already been briefly...like to loo.< it inr. ui4 : 3D ’-- "-: handling of novel language, especially netaphor; az-I i,?i nn rti inriq, -mlerstanding systems: the handling of

Exploiting multiple sources of information in learning an artificial language: human data and modeling.

PubMed

Perruchet, Pierre; Tillmann, Barbara

2010-03-01

This study investigates the joint influences of three factors on the discovery of new word-like units in a continuous artificial speech stream: the statistical structure of the ongoing input, the initial word-likeness of parts of the speech flow, and the contextual information provided by the earlier emergence of other word-like units. Results of an experiment conducted with adult participants show that these sources of information have strong and interactive influences on word discovery. The authors then examine the ability of different models of word segmentation to account for these results. PARSER (Perruchet & Vinter, 1998) is compared to the view that word segmentation relies on the exploitation of transitional probabilities between successive syllables, and with the models based on the Minimum Description Length principle, such as INCDROP. The authors submit arguments suggesting that PARSER has the advantage of accounting for the whole pattern of data without ad-hoc modifications, while relying exclusively on general-purpose learning principles. This study strengthens the growing notion that nonspecific cognitive processes, mainly based on associative learning and memory principles, are able to account for a larger part of early language acquisition than previously assumed. Copyright © 2009 Cognitive Science Society, Inc.

Natural Language Query System Design for Interactive Information Storage and Retrieval Systems. M.S. Thesis

NASA Technical Reports Server (NTRS)

Dominick, Wayne D. (Editor); Liu, I-Hsiung

1985-01-01

The currently developed multi-level language interfaces of information systems are generally designed for experienced users. These interfaces commonly ignore the nature and needs of the largest user group, i.e., casual users. This research identifies the importance of natural language query system research within information storage and retrieval system development; addresses the topics of developing such a query system; and finally, proposes a framework for the development of natural language query systems in order to facilitate the communication between casual users and information storage and retrieval systems.

Intelligent interfaces for expert systems

NASA Technical Reports Server (NTRS)

Villarreal, James A.; Wang, Lui

1988-01-01

Vital to the success of an expert system is an interface to the user which performs intelligently. A generic intelligent interface is being developed for expert systems. This intelligent interface was developed around the in-house developed Expert System for the Flight Analysis System (ESFAS). The Flight Analysis System (FAS) is comprised of 84 configuration controlled FORTRAN subroutines that are used in the preflight analysis of the space shuttle. In order to use FAS proficiently, a person must be knowledgeable in the areas of flight mechanics, the procedures involved in deploying a certain payload, and an overall understanding of the FAS. ESFAS, still in its developmental stage, is taking into account much of this knowledge. The generic intelligent interface involves the integration of a speech recognizer and synthesizer, a preparser, and a natural language parser to ESFAS. The speech recognizer being used is capable of recognizing 1000 words of connected speech. The natural language parser is a commercial software package which uses caseframe instantiation in processing the streams of words from the speech recognizer or the keyboard. The systems configuration is described along with capabilities and drawbacks.

ANTLR Tree Grammar Generator and Extensions

NASA Technical Reports Server (NTRS)

Craymer, Loring

2005-01-01

A computer program implements two extensions of ANTLR (Another Tool for Language Recognition), which is a set of software tools for translating source codes between different computing languages. ANTLR supports predicated- LL(k) lexer and parser grammars, a notation for annotating parser grammars to direct tree construction, and predicated tree grammars. [ LL(k) signifies left-right, leftmost derivation with k tokens of look-ahead, referring to certain characteristics of a grammar.] One of the extensions is a syntax for tree transformations. The other extension is the generation of tree grammars from annotated parser or input tree grammars. These extensions can simplify the process of generating source-to-source language translators and they make possible an approach, called "polyphase parsing," to translation between computing languages. The typical approach to translator development is to identify high-level semantic constructs such as "expressions," "declarations," and "definitions" as fundamental building blocks in the grammar specification used for language recognition. The polyphase approach is to lump ambiguous syntactic constructs during parsing and then disambiguate the alternatives in subsequent tree transformation passes. Polyphase parsing is believed to be useful for generating efficient recognizers for C++ and other languages that, like C++, have significant ambiguities.

Morphosyntactic annotation of CHILDES transcripts*

PubMed Central

SAGAE, KENJI; DAVIS, ERIC; LAVIE, ALON; MACWHINNEY, BRIAN; WINTNER, SHULY

2014-01-01

Corpora of child language are essential for research in child language acquisition and psycholinguistics. Linguistic annotation of the corpora provides researchers with better means for exploring the development of grammatical constructions and their usage. We describe a project whose goal is to annotate the English section of the CHILDES database with grammatical relations in the form of labeled dependency structures. We have produced a corpus of over 18,800 utterances (approximately 65,000 words) with manually curated gold-standard grammatical relation annotations. Using this corpus, we have developed a highly accurate data-driven parser for the English CHILDES data, which we used to automatically annotate the remainder of the English section of CHILDES. We have also extended the parser to Spanish, and are currently working on supporting more languages. The parser and the manually and automatically annotated data are freely available for research purposes. PMID:20334720

An expert system for natural language processing

NASA Technical Reports Server (NTRS)

Hennessy, John F.

1988-01-01

A solution to the natural language processing problem that uses a rule based system, written in OPS5, to replace the traditional parsing method is proposed. The advantage to using a rule based system are explored. Specifically, the extensibility of a rule based solution is discussed as well as the value of maintaining rules that function independently. Finally, the power of using semantics to supplement the syntactic analysis of a sentence is considered.

Artificial intelligence, expert systems, computer vision, and natural language processing

NASA Technical Reports Server (NTRS)

Gevarter, W. B.

1984-01-01

An overview of artificial intelligence (AI), its core ingredients, and its applications is presented. The knowledge representation, logic, problem solving approaches, languages, and computers pertaining to AI are examined, and the state of the art in AI is reviewed. The use of AI in expert systems, computer vision, natural language processing, speech recognition and understanding, speech synthesis, problem solving, and planning is examined. Basic AI topics, including automation, search-oriented problem solving, knowledge representation, and computational logic, are discussed.

CITE NLM: Natural-Language Searching in an Online Catalog.

ERIC Educational Resources Information Center

Doszkocs, Tamas E.

1983-01-01

The National Library of Medicine's Current Information Transfer in English public access online catalog offers unique subject search capabilities--natural-language query input, automatic medical subject headings display, closest match search strategy, ranked document output, dynamic end user feedback for search refinement. References, description…

Incidence Rate of Canonical vs. Derived Medical Terminology in Natural Language.

PubMed

Topac, Vasile; Jurcau, Daniel-Alexandru; Stoicu-Tivadar, Vasile

2015-01-01

Medical terminology appears in the natural language in multiple forms: canonical, derived or inflected form. This research presents an analysis of the form in which medical terminology appears in Romanian and English language. The sources of medical language used for the study are web pages presenting medical information for patients and other lay users. The results show that, in English, medical terminology tends to appear more in canonical form while, in the case of Romanian, it is the opposite. This paper also presents the service that was created to perform this analysis. This tool is available for the general public, and it is designed to be easily extensible, allowing the addition of other languages.

An English language interface for constrained domains

NASA Technical Reports Server (NTRS)

Page, Brenda J.

1989-01-01

The Multi-Satellite Operations Control Center (MSOCC) Jargon Interpreter (MJI) demonstrates an English language interface for a constrained domain. A constrained domain is defined as one with a small and well delineated set of actions and objects. The set of actions chosen for the MJI is from the domain of MSOCC Applications Executive (MAE) Systems Test and Operations Language (STOL) directives and contains directives for signing a cathode ray tube (CRT) on or off, calling up or clearing a display page, starting or stopping a procedure, and controlling history recording. The set of objects chosen consists of CRTs, display pages, STOL procedures, and history files. Translation from English sentences to STOL directives is done in two phases. In the first phase, an augmented transition net (ATN) parser and dictionary are used for determining grammatically correct parsings of input sentences. In the second phase, grammatically typed sentences are submitted to a forward-chaining rule-based system for interpretation and translation into equivalent MAE STOL directives. Tests of the MJI show that it is able to translate individual clearly stated sentences into the subset of directives selected for the prototype. This approach to an English language interface may be used for similarly constrained situations by modifying the MJI's dictionary and rules to reflect the change of domain.

Domain Adaption of Parsing for Operative Notes

PubMed Central

Wang, Yan; Pakhomov, Serguei; Ryan, James O.; Melton, Genevieve B.

2016-01-01

Background Full syntactic parsing of clinical text as a part of clinical natural language processing (NLP) is critical for a wide range of applications, such as identification of adverse drug reactions, patient cohort identification, and gene interaction extraction. Several robust syntactic parsers are publicly available to produce linguistic representations for sentences. However, these existing parsers are mostly trained on general English text and often require adaptation for optimal performance on clinical text. Our objective was to adapt an existing general English parser for the clinical text of operative reports via lexicon augmentation, statistics adjusting, and grammar rules modification based on a set of biomedical text. Method The Stanford unlexicalized probabilistic context-free grammar (PCFG) parser lexicon was expanded with SPECIALIST lexicon along with statistics collected from a limited set of operative notes tagged with a two of POS taggers (GENIA tagger and MedPost). The most frequently occurring verb entries of the SPECIALIST lexicon were adjusted based on manual review of verb usage in operative notes. Stanford parser grammar production rules were also modified based on linguistic features of operative reports. An analogous approach was then applied to the GENIA corpus to test the generalizability of this approach to biomedical text. Results The new unlexicalized PCFG parser extended with the extra lexicon from SPECIALIST along with accurate statistics collected from an operative note corpus tagged with GENIA POS tagger improved the parser performance by 2.26% from 87.64% to 89.90%. There was a progressive improvement with the addition of multiple approaches. Most of the improvement occurred with lexicon augmentation combined with statistics from the operative notes corpus. Application of this approach on the GENIA corpus showed that parsing performance was boosted by 3.81% with a simple new grammar and the addition of the GENIA corpus lexicon

Using natural language processing techniques to inform research on nanotechnology.

PubMed

Lewinski, Nastassja A; McInnes, Bridget T

2015-01-01

Literature in the field of nanotechnology is exponentially increasing with more and more engineered nanomaterials being created, characterized, and tested for performance and safety. With the deluge of published data, there is a need for natural language processing approaches to semi-automate the cataloguing of engineered nanomaterials and their associated physico-chemical properties, performance, exposure scenarios, and biological effects. In this paper, we review the different informatics methods that have been applied to patent mining, nanomaterial/device characterization, nanomedicine, and environmental risk assessment. Nine natural language processing (NLP)-based tools were identified: NanoPort, NanoMapper, TechPerceptor, a Text Mining Framework, a Nanodevice Analyzer, a Clinical Trial Document Classifier, Nanotoxicity Searcher, NanoSifter, and NEIMiner. We conclude with recommendations for sharing NLP-related tools through online repositories to broaden participation in nanoinformatics.

Understanding the Nature of Learners' Out-of-Class Language Learning Experience with Technology

ERIC Educational Resources Information Center

Lai, Chun; Hu, Xiao; Lyu, Boning

2018-01-01

Out-of-class learning with technology comprises an essential context of second language development. Understanding the nature of out-of-class language learning with technology is the initial step towards safeguarding its quality. This study examined the types of learning experiences that language learners engaged in outside the classroom and the…

Dealing with Quantifier Scope Ambiguity in Natural Language Understanding

ERIC Educational Resources Information Center

Hafezi Manshadi, Mohammad

2014-01-01

Quantifier scope disambiguation (QSD) is one of the most challenging problems in deep natural language understanding (NLU) systems. The most popular approach for dealing with QSD is to simply leave the semantic representation (scope-) underspecified and to incrementally add constraints to filter out unwanted readings. Scope underspecification has…

Natural language indicators of differential gene regulation in the human immune system.

PubMed

Mehl, Matthias R; Raison, Charles L; Pace, Thaddeus W W; Arevalo, Jesusa M G; Cole, Steve W

2017-11-21

Adverse social conditions have been linked to a conserved transcriptional response to adversity (CTRA) in circulating leukocytes that may contribute to social gradients in disease. However, the CNS mechanisms involved remain obscure, in part because CTRA gene-expression profiles often track external social-environmental variables more closely than they do self-reported internal affective states such as stress, depression, or anxiety. This study examined the possibility that variations in patterns of natural language use might provide more sensitive indicators of the automatic threat-detection and -response systems that proximally regulate autonomic induction of the CTRA. In 22,627 audio samples of natural speech sampled from the daily interactions of 143 healthy adults, both total language output and patterns of function-word use covaried with CTRA gene expression. These language features predicted CTRA gene expression substantially better than did conventional self-report measures of stress, depression, and anxiety and did so independently of demographic and behavioral factors (age, sex, race, smoking, body mass index) and leukocyte subset distributions. This predictive relationship held when language and gene expression were sampled more than a week apart, suggesting that associations reflect stable individual differences or chronic life circumstances. Given the observed relationship between personal expression and gene expression, patterns of natural language use may provide a useful behavioral indicator of nonconsciously evaluated well-being (implicit safety vs. threat) that is distinct from conscious affective experience and more closely tracks the neurobiological processes involved in peripheral gene regulation. Copyright © 2017 the Author(s). Published by PNAS.

Event construal and temporal distance in natural language.

PubMed

Bhatia, Sudeep; Walasek, Lukasz

2016-07-01

Construal level theory proposes that events that are temporally proximate are represented more concretely than events that are temporally distant. We tested this prediction using two large natural language text corpora. In study 1 we examined posts on Twitter that referenced the future, and found that tweets mentioning temporally proximate dates used more concrete words than those mentioning distant dates. In study 2 we obtained all New York Times articles that referenced U.S. presidential elections between 1987 and 2007. We found that the concreteness of the words in these articles increased with the temporal proximity to their corresponding election. Additionally the reduction in concreteness after the election was much greater than the increase in concreteness leading up to the election, though both changes in concreteness were well described by an exponential function. We replicated this finding with New York Times articles referencing US public holidays. Overall, our results provide strong support for the predictions of construal level theory, and additionally illustrate how large natural language datasets can be used to inform psychological theory. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Learning by Communicating in Natural Language with Conversational Agents

ERIC Educational Resources Information Center

Graesser, Arthur; Li, Haiying; Forsyth, Carol

2014-01-01

Learning is facilitated by conversational interactions both with human tutors and with computer agents that simulate human tutoring and ideal pedagogical strategies. In this article, we describe some intelligent tutoring systems (e.g., AutoTutor) in which agents interact with students in natural language while being sensitive to their cognitive…

Using natural language processing techniques to inform research on nanotechnology

PubMed Central

Lewinski, Nastassja A

2015-01-01

Summary Literature in the field of nanotechnology is exponentially increasing with more and more engineered nanomaterials being created, characterized, and tested for performance and safety. With the deluge of published data, there is a need for natural language processing approaches to semi-automate the cataloguing of engineered nanomaterials and their associated physico-chemical properties, performance, exposure scenarios, and biological effects. In this paper, we review the different informatics methods that have been applied to patent mining, nanomaterial/device characterization, nanomedicine, and environmental risk assessment. Nine natural language processing (NLP)-based tools were identified: NanoPort, NanoMapper, TechPerceptor, a Text Mining Framework, a Nanodevice Analyzer, a Clinical Trial Document Classifier, Nanotoxicity Searcher, NanoSifter, and NEIMiner. We conclude with recommendations for sharing NLP-related tools through online repositories to broaden participation in nanoinformatics. PMID:26199848

SOL - SIZING AND OPTIMIZATION LANGUAGE COMPILER

NASA Technical Reports Server (NTRS)

Scotti, S. J.

1994-01-01

each variable was used. The listings summarize all optimizations, listing the objective functions, design variables, and constraints. The compiler offers error-checking specific to optimization problems, so that simple mistakes will not cost hours of debugging time. The optimization engine used by and included with the SOL compiler is a version of Vanderplatt's ADS system (Version 1.1) modified specifically to work with the SOL compiler. SOL allows the use of the over 100 ADS optimization choices such as Sequential Quadratic Programming, Modified Feasible Directions, interior and exterior penalty function and variable metric methods. Default choices of the many control parameters of ADS are made for the user, however, the user can override any of the ADS control parameters desired for each individual optimization. The SOL language and compiler were developed with an advanced compiler-generation system to ensure correctness and simplify program maintenance. Thus, SOL's syntax was defined precisely by a LALR(1) grammar and the SOL compiler's parser was generated automatically from the LALR(1) grammar with a parser-generator. Hence unlike ad hoc, manually coded interfaces, the SOL compiler's lexical analysis insures that the SOL compiler recognizes all legal SOL programs, can recover from and correct for many errors and report the location of errors to the user. This version of the SOL compiler has been implemented on VAX/VMS computer systems and requires 204 KB of virtual memory to execute. Since the SOL compiler produces FORTRAN code, it requires the VAX FORTRAN compiler to produce an executable program. The SOL compiler consists of 13,000 lines of Pascal code. It was developed in 1986 and last updated in 1988. The ADS and other utility subroutines amount to 14,000 lines of FORTRAN code and were also updated in 1988.

Combining Natural Language Processing and Statistical Text Mining: A Study of Specialized versus Common Languages

ERIC Educational Resources Information Center

Jarman, Jay

2011-01-01

This dissertation focuses on developing and evaluating hybrid approaches for analyzing free-form text in the medical domain. This research draws on natural language processing (NLP) techniques that are used to parse and extract concepts based on a controlled vocabulary. Once important concepts are extracted, additional machine learning algorithms,…

Learning from a Computer Tutor with Natural Language Capabilities

ERIC Educational Resources Information Center

Michael, Joel; Rovick, Allen; Glass, Michael; Zhou, Yujian; Evens, Martha

2003-01-01

CIRCSIM-Tutor is a computer tutor designed to carry out a natural language dialogue with a medical student. Its domain is the baroreceptor reflex, the part of the cardiovascular system that is responsible for maintaining a constant blood pressure. CIRCSIM-Tutor's interaction with students is modeled after the tutoring behavior of two experienced…

The feasibility of using natural language processing to extract clinical information from breast pathology reports.

PubMed

Buckley, Julliette M; Coopey, Suzanne B; Sharko, John; Polubriaginof, Fernanda; Drohan, Brian; Belli, Ahmet K; Kim, Elizabeth M H; Garber, Judy E; Smith, Barbara L; Gadd, Michele A; Specht, Michelle C; Roche, Constance A; Gudewicz, Thomas M; Hughes, Kevin S

2012-01-01

The opportunity to integrate clinical decision support systems into clinical practice is limited due to the lack of structured, machine readable data in the current format of the electronic health record. Natural language processing has been designed to convert free text into machine readable data. The aim of the current study was to ascertain the feasibility of using natural language processing to extract clinical information from >76,000 breast pathology reports. APPROACH AND PROCEDURE: Breast pathology reports from three institutions were analyzed using natural language processing software (Clearforest, Waltham, MA) to extract information on a variety of pathologic diagnoses of interest. Data tables were created from the extracted information according to date of surgery, side of surgery, and medical record number. The variety of ways in which each diagnosis could be represented was recorded, as a means of demonstrating the complexity of machine interpretation of free text. There was widespread variation in how pathologists reported common pathologic diagnoses. We report, for example, 124 ways of saying invasive ductal carcinoma and 95 ways of saying invasive lobular carcinoma. There were >4000 ways of saying invasive ductal carcinoma was not present. Natural language processor sensitivity and specificity were 99.1% and 96.5% when compared to expert human coders. We have demonstrated how a large body of free text medical information such as seen in breast pathology reports, can be converted to a machine readable format using natural language processing, and described the inherent complexities of the task.

Natural language processing: an introduction.

PubMed

Nadkarni, Prakash M; Ohno-Machado, Lucila; Chapman, Wendy W

2011-01-01

To provide an overview and tutorial of natural language processing (NLP) and modern NLP-system design. This tutorial targets the medical informatics generalist who has limited acquaintance with the principles behind NLP and/or limited knowledge of the current state of the art. We describe the historical evolution of NLP, and summarize common NLP sub-problems in this extensive field. We then provide a synopsis of selected highlights of medical NLP efforts. After providing a brief description of common machine-learning approaches that are being used for diverse NLP sub-problems, we discuss how modern NLP architectures are designed, with a summary of the Apache Foundation's Unstructured Information Management Architecture. We finally consider possible future directions for NLP, and reflect on the possible impact of IBM Watson on the medical field.

The Nature of Object Marking in American Sign Language

ERIC Educational Resources Information Center

Gokgoz, Kadir

2013-01-01

In this dissertation, I examine the nature of object marking in American Sign Language (ASL). I investigate object marking by means of directionality (the movement of the verb towards a certain location in signing space) and by means of handling classifiers (certain handshapes accompanying the verb). I propose that object marking in ASL is…

Natural Environment Language Assessment and Intervention with Severely Impaired Preschoolers.

ERIC Educational Resources Information Center

Halle, James W.; And Others

1984-01-01

The paper presents a rationale for assessing and intervening with severely impaired preschoolers in the natural environment, identifies three prerequisites for language training (content and motivation, reinforcing social and physical environment, and a communicative repertoire), and examines two levels of intervention. (CL)

Structure before Meaning: Sentence Processing, Plausibility, and Subcategorization

PubMed Central

Kizach, Johannes; Nyvad, Anne Mette; Christensen, Ken Ramshøj

2013-01-01

Natural language processing is a fast and automatized process. A crucial part of this process is parsing, the online incremental construction of a syntactic structure. The aim of this study was to test whether a wh-filler extracted from an embedded clause is initially attached as the object of the matrix verb with subsequent reanalysis, and if so, whether the plausibility of such an attachment has an effect on reaction time. Finally, we wanted to examine whether subcategorization plays a role. We used a method called G-Maze to measure response time in a self-paced reading design. The experiments confirmed that there is early attachment of fillers to the matrix verb. When this attachment is implausible, the off-line acceptability of the whole sentence is significantly reduced. The on-line results showed that G-Maze was highly suited for this type of experiment. In accordance with our predictions, the results suggest that the parser ignores (or has no access to information about) implausibility and attaches fillers as soon as possible to the matrix verb. However, the results also show that the parser uses the subcategorization frame of the matrix verb. In short, the parser ignores semantic information and allows implausible attachments but adheres to information about which type of object a verb can take, ensuring that the parser does not make impossible attachments. We argue that the evidence supports a syntactic parser informed by syntactic cues, rather than one guided by semantic cues or one that is blind, or completely autonomous. PMID:24116101

Structure before meaning: sentence processing, plausibility, and subcategorization.

PubMed

Kizach, Johannes; Nyvad, Anne Mette; Christensen, Ken Ramshøj

2013-01-01

Natural language processing is a fast and automatized process. A crucial part of this process is parsing, the online incremental construction of a syntactic structure. The aim of this study was to test whether a wh-filler extracted from an embedded clause is initially attached as the object of the matrix verb with subsequent reanalysis, and if so, whether the plausibility of such an attachment has an effect on reaction time. Finally, we wanted to examine whether subcategorization plays a role. We used a method called G-Maze to measure response time in a self-paced reading design. The experiments confirmed that there is early attachment of fillers to the matrix verb. When this attachment is implausible, the off-line acceptability of the whole sentence is significantly reduced. The on-line results showed that G-Maze was highly suited for this type of experiment. In accordance with our predictions, the results suggest that the parser ignores (or has no access to information about) implausibility and attaches fillers as soon as possible to the matrix verb. However, the results also show that the parser uses the subcategorization frame of the matrix verb. In short, the parser ignores semantic information and allows implausible attachments but adheres to information about which type of object a verb can take, ensuring that the parser does not make impossible attachments. We argue that the evidence supports a syntactic parser informed by syntactic cues, rather than one guided by semantic cues or one that is blind, or completely autonomous.

Paradigms of Evaluation in Natural Language Processing: Field Linguistics for Glass Box Testing

ERIC Educational Resources Information Center

Cohen, Kevin Bretonnel

2010-01-01

Although software testing has been well-studied in computer science, it has received little attention in natural language processing. Nonetheless, a fully developed methodology for glass box evaluation and testing of language processing applications already exists in the field methods of descriptive linguistics. This work lays out a number of…

Categorization of Survey Text Utilizing Natural Language Processing and Demographic Filtering

DTIC Science & Technology

2017-09-01

SURVEY TEXT UTILIZING NATURAL LANGUAGE PROCESSING AND DEMOGRAPHIC FILTERING by Christine M. Cairoli September 2017 Thesis Advisor: Lyn...DATE September 2017 3. REPORT TYPE AND DATES COVERED Master’s thesis 4. TITLE AND SUBTITLE CATEGORIZATION OF SURVEY TEXT UTILIZING NATURAL...words) Thousands of Navy survey free text comments are overlooked every year because reading and interpreting comments is expensive, time consuming

Natural Language Processing in Radiology: A Systematic Review.

PubMed

Pons, Ewoud; Braun, Loes M M; Hunink, M G Myriam; Kors, Jan A

2016-05-01

Radiological reporting has generated large quantities of digital content within the electronic health record, which is potentially a valuable source of information for improving clinical care and supporting research. Although radiology reports are stored for communication and documentation of diagnostic imaging, harnessing their potential requires efficient and automated information extraction: they exist mainly as free-text clinical narrative, from which it is a major challenge to obtain structured data. Natural language processing (NLP) provides techniques that aid the conversion of text into a structured representation, and thus enables computers to derive meaning from human (ie, natural language) input. Used on radiology reports, NLP techniques enable automatic identification and extraction of information. By exploring the various purposes for their use, this review examines how radiology benefits from NLP. A systematic literature search identified 67 relevant publications describing NLP methods that support practical applications in radiology. This review takes a close look at the individual studies in terms of tasks (ie, the extracted information), the NLP methodology and tools used, and their application purpose and performance results. Additionally, limitations, future challenges, and requirements for advancing NLP in radiology will be discussed. (©) RSNA, 2016 Online supplemental material is available for this article.

The Exploring Nature of Definitions and Classifications of Language Learning Strategies (LLSs) in the Current Studies of Second/Foreign Language Learning

ERIC Educational Resources Information Center

Fazeli, Seyed Hossein

2011-01-01

This study aims to explore the nature of definitions and classifications of Language Learning Strategies (LLSs) in the current studies of second/foreign language learning in order to show the current problems regarding such definitions and classifications. The present study shows that there is not a universal agreeable definition and…

A study of the transferability of influenza case detection systems between two large healthcare systems

PubMed Central

Wagner, Michael M.; Cooper, Gregory F.; Ferraro, Jeffrey P.; Su, Howard; Gesteland, Per H.; Haug, Peter J.; Millett, Nicholas E.; Aronis, John M.; Nowalk, Andrew J.; Ruiz, Victor M.; López Pineda, Arturo; Shi, Lingyun; Van Bree, Rudy; Ginter, Thomas; Tsui, Fuchiang

2017-01-01

Objectives This study evaluates the accuracy and transferability of Bayesian case detection systems (BCD) that use clinical notes from emergency department (ED) to detect influenza cases. Methods A BCD uses natural language processing (NLP) to infer the presence or absence of clinical findings from ED notes, which are fed into a Bayesain network classifier (BN) to infer patients’ diagnoses. We developed BCDs at the University of Pittsburgh Medical Center (BCDUPMC) and Intermountain Healthcare in Utah (BCDIH). At each site, we manually built a rule-based NLP and trained a Bayesain network classifier from over 40,000 ED encounters between Jan. 2008 and May. 2010 using feature selection, machine learning, and expert debiasing approach. Transferability of a BCD in this study may be impacted by seven factors: development (source) institution, development parser, application (target) institution, application parser, NLP transfer, BN transfer, and classification task. We employed an ANOVA analysis to study their impacts on BCD performance. Results Both BCDs discriminated well between influenza and non-influenza on local test cases (AUCs > 0.92). When tested for transferability using the other institution’s cases, BCDUPMC discriminations declined minimally (AUC decreased from 0.95 to 0.94, p<0.01), and BCDIH discriminations declined more (from 0.93 to 0.87, p<0.0001). We attributed the BCDIH decline to the lower recall of the IH parser on UPMC notes. The ANOVA analysis showed five significant factors: development parser, application institution, application parser, BN transfer, and classification task. Conclusion We demonstrated high influenza case detection performance in two large healthcare systems in two geographically separated regions, providing evidentiary support for the use of automated case detection from routinely collected electronic clinical notes in national influenza surveillance. The transferability could be improved by training Bayesian network

A study of the transferability of influenza case detection systems between two large healthcare systems.

PubMed

Ye, Ye; Wagner, Michael M; Cooper, Gregory F; Ferraro, Jeffrey P; Su, Howard; Gesteland, Per H; Haug, Peter J; Millett, Nicholas E; Aronis, John M; Nowalk, Andrew J; Ruiz, Victor M; López Pineda, Arturo; Shi, Lingyun; Van Bree, Rudy; Ginter, Thomas; Tsui, Fuchiang

2017-01-01

This study evaluates the accuracy and transferability of Bayesian case detection systems (BCD) that use clinical notes from emergency department (ED) to detect influenza cases. A BCD uses natural language processing (NLP) to infer the presence or absence of clinical findings from ED notes, which are fed into a Bayesain network classifier (BN) to infer patients' diagnoses. We developed BCDs at the University of Pittsburgh Medical Center (BCDUPMC) and Intermountain Healthcare in Utah (BCDIH). At each site, we manually built a rule-based NLP and trained a Bayesain network classifier from over 40,000 ED encounters between Jan. 2008 and May. 2010 using feature selection, machine learning, and expert debiasing approach. Transferability of a BCD in this study may be impacted by seven factors: development (source) institution, development parser, application (target) institution, application parser, NLP transfer, BN transfer, and classification task. We employed an ANOVA analysis to study their impacts on BCD performance. Both BCDs discriminated well between influenza and non-influenza on local test cases (AUCs > 0.92). When tested for transferability using the other institution's cases, BCDUPMC discriminations declined minimally (AUC decreased from 0.95 to 0.94, p<0.01), and BCDIH discriminations declined more (from 0.93 to 0.87, p<0.0001). We attributed the BCDIH decline to the lower recall of the IH parser on UPMC notes. The ANOVA analysis showed five significant factors: development parser, application institution, application parser, BN transfer, and classification task. We demonstrated high influenza case detection performance in two large healthcare systems in two geographically separated regions, providing evidentiary support for the use of automated case detection from routinely collected electronic clinical notes in national influenza surveillance. The transferability could be improved by training Bayesian network classifier locally and increasing the accuracy of

'Fly Like This': Natural Language Interface for UAV Mission Planning

NASA Technical Reports Server (NTRS)

Chandarana, Meghan; Meszaros, Erica L.; Trujillo, Anna; Allen, B. Danette

2017-01-01

With the increasing presence of unmanned aerial vehicles (UAVs) in everyday environments, the user base of these powerful and potentially intelligent machines is expanding beyond exclusively highly trained vehicle operators to include non-expert system users. Scientists seeking to augment costly and often inflexible methods of data collection historically used are turning towards lower cost and reconfigurable UAVs. These new users require more intuitive and natural methods for UAV mission planning. This paper explores two natural language interfaces - gesture and speech - for UAV flight path generation through individual user studies. Subjects who participated in the user studies also used a mouse-based interface for a baseline comparison. Each interface allowed the user to build flight paths from a library of twelve individual trajectory segments. Individual user studies evaluated performance, efficacy, and ease-of-use of each interface using background surveys, subjective questionnaires, and observations on time and correctness. Analysis indicates that natural language interfaces are promising alternatives to traditional interfaces. The user study data collected on the efficacy and potential of each interface will be used to inform future intuitive UAV interface design for non-expert users.

Exploiting Lexical Regularities in Designing Natural Language Systems.

DTIC Science & Technology

1988-04-01

ELEMENT. PROJECT. TASKN Artificial Inteligence Laboratory A1A4WR NTumet 0) 545 Technology Square Cambridge, MA 02139 Ln *t- CONTROLLING OFFICE NAME AND...RO-RI95 922 EXPLOITING LEXICAL REGULARITIES IN DESIGNING NATURAL 1/1 LANGUAGE SYSTENS(U) MASSACHUSETTS INST OF TECH CAMBRIDGE ARTIFICIAL INTELLIGENCE...oes.ary and ftdou.Ip hr Nl wow" L,2This paper presents the lexical component of the START Question Answering system developed at the MIT Artificial

Studying Associations Between Heart Failure Self-Management and Rehospitalizations Using Natural Language Processing.

PubMed

Topaz, Maxim; Radhakrishnan, Kavita; Blackley, Suzanne; Lei, Victor; Lai, Kenneth; Zhou, Li

2016-09-14

This study developed an innovative natural language processing algorithm to automatically identify heart failure (HF) patients with ineffective self-management status (in the domains of diet, physical activity, medication adherence, and adherence to clinician appointments) from narrative discharge summary notes. We also analyzed the association between self-management status and preventable 30-day hospital readmissions. Our natural language system achieved relatively high accuracy (F-measure = 86.3%; precision = 95%; recall = 79.2%) on a testing sample of 300 notes annotated by two human reviewers. In a sample of 8,901 HF patients admitted to our healthcare system, 14.4% (n = 1,282) had documentation of ineffective HF self-management. Adjusted regression analyses indicated that presence of any skill-related self-management deficit (odds ratio [OR] = 1.3, 95% confidence interval [CI] = [1.1, 1.6]) and non-specific ineffective self-management (OR = 1.5, 95% CI = [1.2, 2]) was significantly associated with readmissions. We have demonstrated the feasibility of identifying ineffective HF self-management from electronic discharge summaries with natural language processing. © The Author(s) 2016.

An ontology model for nursing narratives with natural language generation technology.

PubMed

Min, Yul Ha; Park, Hyeoun-Ae; Jeon, Eunjoo; Lee, Joo Yun; Jo, Soo Jung

2013-01-01

The purpose of this study was to develop an ontology model to generate nursing narratives as natural as human language from the entity-attribute-value triplets of a detailed clinical model using natural language generation technology. The model was based on the types of information and documentation time of the information along the nursing process. The typesof information are data characterizing the patient status, inferences made by the nurse from the patient data, and nursing actions selected by the nurse to change the patient status. This information was linked to the nursing process based on the time of documentation. We describe a case study illustrating the application of this model in an acute-care setting. The proposed model provides a strategy for designing an electronic nursing record system.

Automated detection using natural language processing of radiologists recommendations for additional imaging of incidental findings.

PubMed

Dutta, Sayon; Long, William J; Brown, David F M; Reisner, Andrew T

2013-08-01

As use of radiology studies increases, there is a concurrent increase in incidental findings (eg, lung nodules) for which the radiologist issues recommendations for additional imaging for follow-up. Busy emergency physicians may be challenged to carefully communicate recommendations for additional imaging not relevant to the patient's primary evaluation. The emergence of electronic health records and natural language processing algorithms may help address this quality gap. We seek to describe recommendations for additional imaging from our institution and develop and validate an automated natural language processing algorithm to reliably identify recommendations for additional imaging. We developed a natural language processing algorithm to detect recommendations for additional imaging, using 3 iterative cycles of training and validation. The third cycle used 3,235 radiology reports (1,600 for algorithm training and 1,635 for validation) of discharged emergency department (ED) patients from which we determined the incidence of discharge-relevant recommendations for additional imaging and the frequency of appropriate discharge documentation. The test characteristics of the 3 natural language processing algorithm iterations were compared, using blinded chart review as the criterion standard. Discharge-relevant recommendations for additional imaging were found in 4.5% (95% confidence interval [CI] 3.5% to 5.5%) of ED radiology reports, but 51% (95% CI 43% to 59%) of discharge instructions failed to note those findings. The final natural language processing algorithm had 89% (95% CI 82% to 94%) sensitivity and 98% (95% CI 97% to 98%) specificity for detecting recommendations for additional imaging. For discharge-relevant recommendations for additional imaging, sensitivity improved to 97% (95% CI 89% to 100%). Recommendations for additional imaging are common, and failure to document relevant recommendations for additional imaging in ED discharge instructions occurs

Natural language processing: an introduction

PubMed Central

Ohno-Machado, Lucila; Chapman, Wendy W

2011-01-01

Objectives To provide an overview and tutorial of natural language processing (NLP) and modern NLP-system design. Target audience This tutorial targets the medical informatics generalist who has limited acquaintance with the principles behind NLP and/or limited knowledge of the current state of the art. Scope We describe the historical evolution of NLP, and summarize common NLP sub-problems in this extensive field. We then provide a synopsis of selected highlights of medical NLP efforts. After providing a brief description of common machine-learning approaches that are being used for diverse NLP sub-problems, we discuss how modern NLP architectures are designed, with a summary of the Apache Foundation's Unstructured Information Management Architecture. We finally consider possible future directions for NLP, and reflect on the possible impact of IBM Watson on the medical field. PMID:21846786

Understanding natural language for spacecraft sequencing

NASA Technical Reports Server (NTRS)

Katz, Boris; Brooks, Robert N., Jr.

1987-01-01

The paper describes a natural language understanding system, START, that translates English text into a knowledge base. The understanding and the generating modules of START share a Grammar which is built upon reversible transformations. Users can retrieve information by querying the knowledge base in English; the system then produces an English response. START can be easily adapted to many different domains. One such domain is spacecraft sequencing. A high-level overview of sequencing as it is practiced at JPL is presented in the paper, and three areas within this activity are identified for potential application of the START system. Examples are given of an actual dialog with START based on simulated data for the Mars Observer mission.

Natural Language Processing and Game-Based Practice in iSTART

ERIC Educational Resources Information Center

Jackson, G. Tanner; Boonthum-Denecke, Chutima; McNamara, Danielle S.

2015-01-01

Intelligent Tutoring Systems (ITSs) are situated in a potential struggle between effective pedagogy and system enjoyment and engagement. iSTART, a reading strategy tutoring system in which students practice generating self-explanations and using reading strategies, employs two devices to engage the user. The first is natural language processing…

Natural Language Processing Technologies in Radiology Research and Clinical Applications.

PubMed

Cai, Tianrun; Giannopoulos, Andreas A; Yu, Sheng; Kelil, Tatiana; Ripley, Beth; Kumamaru, Kanako K; Rybicki, Frank J; Mitsouras, Dimitrios

2016-01-01

The migration of imaging reports to electronic medical record systems holds great potential in terms of advancing radiology research and practice by leveraging the large volume of data continuously being updated, integrated, and shared. However, there are significant challenges as well, largely due to the heterogeneity of how these data are formatted. Indeed, although there is movement toward structured reporting in radiology (ie, hierarchically itemized reporting with use of standardized terminology), the majority of radiology reports remain unstructured and use free-form language. To effectively "mine" these large datasets for hypothesis testing, a robust strategy for extracting the necessary information is needed. Manual extraction of information is a time-consuming and often unmanageable task. "Intelligent" search engines that instead rely on natural language processing (NLP), a computer-based approach to analyzing free-form text or speech, can be used to automate this data mining task. The overall goal of NLP is to translate natural human language into a structured format (ie, a fixed collection of elements), each with a standardized set of choices for its value, that is easily manipulated by computer programs to (among other things) order into subcategories or query for the presence or absence of a finding. The authors review the fundamentals of NLP and describe various techniques that constitute NLP in radiology, along with some key applications. ©RSNA, 2016.

Natural Language Processing Technologies in Radiology Research and Clinical Applications

PubMed Central

Cai, Tianrun; Giannopoulos, Andreas A.; Yu, Sheng; Kelil, Tatiana; Ripley, Beth; Kumamaru, Kanako K.; Rybicki, Frank J.

2016-01-01

The migration of imaging reports to electronic medical record systems holds great potential in terms of advancing radiology research and practice by leveraging the large volume of data continuously being updated, integrated, and shared. However, there are significant challenges as well, largely due to the heterogeneity of how these data are formatted. Indeed, although there is movement toward structured reporting in radiology (ie, hierarchically itemized reporting with use of standardized terminology), the majority of radiology reports remain unstructured and use free-form language. To effectively “mine” these large datasets for hypothesis testing, a robust strategy for extracting the necessary information is needed. Manual extraction of information is a time-consuming and often unmanageable task. “Intelligent” search engines that instead rely on natural language processing (NLP), a computer-based approach to analyzing free-form text or speech, can be used to automate this data mining task. The overall goal of NLP is to translate natural human language into a structured format (ie, a fixed collection of elements), each with a standardized set of choices for its value, that is easily manipulated by computer programs to (among other things) order into subcategories or query for the presence or absence of a finding. The authors review the fundamentals of NLP and describe various techniques that constitute NLP in radiology, along with some key applications. ©RSNA, 2016 PMID:26761536

Query2Question: Translating Visualization Interaction into Natural Language.

PubMed

Nafari, Maryam; Weaver, Chris

2015-06-01

Richly interactive visualization tools are increasingly popular for data exploration and analysis in a wide variety of domains. Existing systems and techniques for recording provenance of interaction focus either on comprehensive automated recording of low-level interaction events or on idiosyncratic manual transcription of high-level analysis activities. In this paper, we present the architecture and translation design of a query-to-question (Q2Q) system that automatically records user interactions and presents them semantically using natural language (written English). Q2Q takes advantage of domain knowledge and uses natural language generation (NLG) techniques to translate and transcribe a progression of interactive visualization states into a visual log of styled text that complements and effectively extends the functionality of visualization tools. We present Q2Q as a means to support a cross-examination process in which questions rather than interactions are the focus of analytic reasoning and action. We describe the architecture and implementation of the Q2Q system, discuss key design factors and variations that effect question generation, and present several visualizations that incorporate Q2Q for analysis in a variety of knowledge domains.

Intelligent agents as a basis for natural language interfaces

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chin, D.N.

1987-01-01

Typical natural-language interfaces respond passively to the users's commands and queries. They cannot volunteer information, correction user misconceptions, or reject unethical requests. In order to do these things, a system must be an intelligent agent. UC (UNIX Consultant), a natural language system that helps the user solve problems in using the UNIX operating system, is such an intelligent agent. The agent component of UC in UCEgo. UCEgo provides UC with its own goals and plans. By adopting different goals in different situations, UCEgo creates and executes different plans, enabling it to interact appropriately with the user. UCEgo adopts goals frommore » its themes, adopts subgoals during planning, and adopts metagoals for dealing with goal interactions. It also adopts goals when it notices that the user either lacks necessary knowledge, or has incorrect beliefs. In these cases, UCEgo plans to volunteer information or correct the user's misconception as appropriate. The user's knowledge and beliefs are modeled by the KNOME (KNOwledge Model of Expertise) component of UC. KNOME is a double-stereotype system which categorizes users by expertise and categorizes UNIX facts by difficulty.« less

The Boolean Is Dead, Long Live the Boolean! Natural Language versus Boolean Searching in Introductory Undergraduate Instruction

ERIC Educational Resources Information Center

Lowe, M. Sara; Maxson, Bronwen K.; Stone, Sean M.; Miller, Willie; Snajdr, Eric; Hanna, Kathleen

2018-01-01

Boolean logic can be a difficult concept for first-year, introductory students to grasp. This paper compares the results of Boolean and natural language searching across several databases with searches created from student research questions. Performance differences between databases varied. Overall, natural search language is at least as good as…

Natural language from artificial life.

PubMed

Kirby, Simon

2002-01-01

This article aims to show that linguistics, in particular the study of the lexico-syntactic aspects of language, provides fertile ground for artificial life modeling. A survey of the models that have been developed over the last decade and a half is presented to demonstrate that ALife techniques have a lot to offer an explanatory theory of language. It is argued that this is because much of the structure of language is determined by the interaction of three complex adaptive systems: learning, culture, and biological evolution. Computational simulation, informed by theoretical linguistics, is an appropriate response to the challenge of explaining real linguistic data in terms of the processes that underpin human language.

Analyzing Discourse Processing Using a Simple Natural Language Processing Tool

ERIC Educational Resources Information Center

Crossley, Scott A.; Allen, Laura K.; Kyle, Kristopher; McNamara, Danielle S.

2014-01-01

Natural language processing (NLP) provides a powerful approach for discourse processing researchers. However, there remains a notable degree of hesitation by some researchers to consider using NLP, at least on their own. The purpose of this article is to introduce and make available a "simple" NLP (SiNLP) tool. The overarching goal of…

Subgroups in Language Trajectories from 4 to 11 Years: The Nature and Predictors of Stable, Improving and Decreasing Language Trajectory Groups

ERIC Educational Resources Information Center

McKean, Cristina; Wraith, Darren; Eadie, Patricia; Cook, Fallon; Mensah, Fiona; Reilly, Sheena

2017-01-01

Background: Little is known about the nature, range and prevalence of different subgroups in language trajectories extant in a population from 4 to 11 years. This hinders strategic targeting and design of interventions, particularly targeting those whose difficulties will likely persist. Methods: Children's language abilities from 4 to 11 years…

SWAN: An expert system with natural language interface for tactical air capability assessment

NASA Technical Reports Server (NTRS)

Simmons, Robert M.

1987-01-01

SWAN is an expert system and natural language interface for assessing the war fighting capability of Air Force units in Europe. The expert system is an object oriented knowledge based simulation with an alternate worlds facility for performing what-if excursions. Responses from the system take the form of generated text, tables, or graphs. The natural language interface is an expert system in its own right, with a knowledge base and rules which understand how to access external databases, models, or expert systems. The distinguishing feature of the Air Force expert system is its use of meta-knowledge to generate explanations in the frame and procedure based environment.

Exploring culture, language and the perception of the nature of science

NASA Astrophysics Data System (ADS)

Sutherland, Dawn

2002-01-01

One dimension of early Canadian education is the attempt of the government to use the education system as an assimilative tool to integrate the First Nations and Me´tis people into Euro-Canadian society. Despite these attempts, many First Nations and Me´tis people retained their culture and their indigenous language. Few science educators have examined First Nations and Western scientific worldviews and the impact they may have on science learning. This study explored the views some First Nations (Cree) and Euro-Canadian Grade-7-level students in Manitoba had about the nature of science. Both qualitative (open-ended questions and interviews) and quantitative (a Likert-scale questionnaire) instruments were used to explore student views. A central hypothesis to this research programme is the possibility that the different world-views of two student populations, Cree and Euro-Canadian, are likely to influence their perceptions of science. This preliminary study explored a range of methodologies to probe the perceptions of the nature of science in these two student populations. It was found that the two cultural groups differed significantly between some of the tenets in a Nature of Scientific Knowledge Scale (NSKS). Cree students significantly differed from Euro-Canadian students on the developmental, testable and unified tenets of the nature of scientific knowledge scale. No significant differences were found in NSKS scores between language groups (Cree students who speak English in the home and those who speak English and Cree or Cree only). The differences found between language groups were primarily in the open-ended questions where preformulated responses were absent. Interviews about critical incidents provided more detailed accounts of the Cree students' perception of the nature of science. The implications of the findings of this study are discussed in relation to the challenges related to research methodology, further areas for investigation, science

Recurrent Artificial Neural Networks and Finite State Natural Language Processing.

ERIC Educational Resources Information Center

Moisl, Hermann

It is argued that pessimistic assessments of the adequacy of artificial neural networks (ANNs) for natural language processing (NLP) on the grounds that they have a finite state architecture are unjustified, and that their adequacy in this regard is an empirical issue. First, arguments that counter standard objections to finite state NLP on the…

Advanced Natural Language Processing and Temporal Mining for Clinical Discovery

ERIC Educational Resources Information Center

Mehrabi, Saeed

2016-01-01

There has been vast and growing amount of healthcare data especially with the rapid adoption of electronic health records (EHRs) as a result of the HITECH act of 2009. It is estimated that around 80% of the clinical information resides in the unstructured narrative of an EHR. Recently, natural language processing (NLP) techniques have offered…

Natural Language Processing as a Discipline at LLNL

DOE Office of Scientific and Technical Information (OSTI.GOV)

Firpo, M A

The field of Natural Language Processing (NLP) is described as it applies to the needs of LLNL in handling free-text. The state of the practice is outlined with the emphasis placed on two specific aspects of NLP: Information Extraction and Discourse Integration. A brief description is included of the NLP applications currently being used at LLNL. A gap analysis provides a look at where the technology needs work in order to meet the needs of LLNL. Finally, recommendations are made to meet these needs.

Research at Yale in Natural Language Processing. Research Report #84.

ERIC Educational Resources Information Center

Schank, Roger C.

This report summarizes the capabilities of five computer programs at Yale that do automatic natural language processing as of the end of 1976. For each program an introduction to its overall intent is given, followed by the input/output, a short discussion of the research underlying the program, and a prognosis for future development. The programs…

Natural Language Processing: A Tutorial. Revision

DTIC Science & Technology

1990-01-01

English in word-for-word language translations. An oft-repeated (although fictional) anecdote illustrates the ... English by a language translation program, became: " The vodka is strong but 3 the steak is rotten." The point made is that vast amounts of knowledge...are required for effective language translations. The initial goal for Language Translation was "fully-automatic high-quality translation" (FAHOT).

Development and Evaluation of a Thai Learning System on the Web Using Natural Language Processing.

ERIC Educational Resources Information Center

Dansuwan, Suyada; Nishina, Kikuko; Akahori, Kanji; Shimizu, Yasutaka

2001-01-01

Describes the Thai Learning System, which is designed to help learners acquire the Thai word order system. The system facilitates the lessons on the Web using HyperText Markup Language and Perl programming, which interfaces with natural language processing by means of Prolog. (Author/VWL)

A general natural-language text processor for clinical radiology.

PubMed Central

Friedman, C; Alderson, P O; Austin, J H; Cimino, J J; Johnson, S B

1994-01-01

OBJECTIVE: Development of a general natural-language processor that identifies clinical information in narrative reports and maps that information into a structured representation containing clinical terms. DESIGN: The natural-language processor provides three phases of processing, all of which are driven by different knowledge sources. The first phase performs the parsing. It identifies the structure of the text through use of a grammar that defines semantic patterns and a target form. The second phase, regularization, standardizes the terms in the initial target structure via a compositional mapping of multi-word phrases. The third phase, encoding, maps the terms to a controlled vocabulary. Radiology is the test domain for the processor and the target structure is a formal model for representing clinical information in that domain. MEASUREMENTS: The impression sections of 230 radiology reports were encoded by the processor. Results of an automated query of the resultant database for the occurrences of four diseases were compared with the analysis of a panel of three physicians to determine recall and precision. RESULTS: Without training specific to the four diseases, recall and precision of the system (combined effect of the processor and query generator) were 70% and 87%. Training of the query component increased recall to 85% without changing precision. PMID:7719797

Verification Processes in Recognition Memory: The Role of Natural Language Mediators

ERIC Educational Resources Information Center

Marshall, Philip H.; Smith, Randolph A. S.

1977-01-01

The existence of verification processes in recognition memory was confirmed in the context of Adams' (Adams & Bray, 1970) closed-loop theory. Subjects' recognition was tested following a learning session. The expectation was that data would reveal consistent internal relationships supporting the position that natural language mediation plays…

Teaching the tacit knowledge of programming to noviceswith natural language tutoring

NASA Astrophysics Data System (ADS)

Lane, H. Chad; Vanlehn, Kurt

2005-09-01

For beginning programmers, inadequate problem solving and planning skills are among the most salient of their weaknesses. In this paper, we test the efficacy of natural language tutoring to teach and scaffold acquisition of these skills. We describe ProPL (Pro-PELL), a dialogue-based intelligent tutoring system that elicits goal decompositions and program plans from students in natural language. The system uses a variety of tutoring tactics that leverage students' intuitive understandings of the problem, how it might be solved, and the underlying concepts of programming. We report the results of a small-scale evaluation comparing students who used ProPL with a control group who read the same content. Our primary findings are that students who received tutoring from ProPL seem to have developed an improved ability to solve the composition problem and displayed behaviors that suggest they were able to think at greater levels of abstraction than students in the read-only group.

Using the Natural Language Paradigm (NLP) to Increase Vocalizations of Older Adults with Cognitive Impairments

ERIC Educational Resources Information Center

LeBlanc, Linda A.; Geiger, Kaneen B.; Sautter, Rachael A.; Sidener, Tina M.

2007-01-01

The Natural Language Paradigm (NLP) has proven effective in increasing spontaneous verbalizations for children with autism. This study investigated the use of NLP with older adults with cognitive impairments served at a leisure-based adult day program for seniors. Three individuals with limited spontaneous use of functional language participated…

One grammar or two? Sign Languages and the Nature of Human Language

PubMed Central

Lillo-Martin, Diane C; Gajewski, Jon

2014-01-01

Linguistic research has identified abstract properties that seem to be shared by all languages—such properties may be considered defining characteristics. In recent decades, the recognition that human language is found not only in the spoken modality but also in the form of sign languages has led to a reconsideration of some of these potential linguistic universals. In large part, the linguistic analysis of sign languages has led to the conclusion that universal characteristics of language can be stated at an abstract enough level to include languages in both spoken and signed modalities. For example, languages in both modalities display hierarchical structure at sub-lexical and phrasal level, and recursive rule application. However, this does not mean that modality-based differences between signed and spoken languages are trivial. In this article, we consider several candidate domains for modality effects, in light of the overarching question: are signed and spoken languages subject to the same abstract grammatical constraints, or is a substantially different conception of grammar needed for the sign language case? We look at differences between language types based on the use of space, iconicity, and the possibility for simultaneity in linguistic expression. The inclusion of sign languages does support some broadening of the conception of human language—in ways that are applicable for spoken languages as well. Still, the overall conclusion is that one grammar applies for human language, no matter the modality of expression. PMID:25013534

Analyzing Learner Language: Towards a Flexible Natural Language Processing Architecture for Intelligent Language Tutors

ERIC Educational Resources Information Center

Amaral, Luiz; Meurers, Detmar; Ziai, Ramon

2011-01-01

Intelligent language tutoring systems (ILTS) typically analyze learner input to diagnose learner language properties and provide individualized feedback. Despite a long history of ILTS research, such systems are virtually absent from real-life foreign language teaching (FLT). Taking a step toward more closely linking ILTS research to real-life…

Real English: A Translator to Enable Natural Language Man-Machine Conversation.

ERIC Educational Resources Information Center

Gautin, Harvey

This dissertation presents a pragmatic interpreter/translator called Real English to serve as a natural language man-machine communication interface in a multi-mode on-line information retrieval system. This multi-mode feature affords the user a library-like searching tool by giving him access to a dictionary, lexicon, thesaurus, synonym table,…

The Application of Natural Language Processing to Augmentative and Alternative Communication

ERIC Educational Resources Information Center

Higginbotham, D. Jeffery; Lesher, Gregory W.; Moulton, Bryan J.; Roark, Brian

2012-01-01

Significant progress has been made in the application of natural language processing (NLP) to augmentative and alternative communication (AAC), particularly in the areas of interface design and word prediction. This article will survey the current state-of-the-science of NLP in AAC and discuss its future applications for the development of next…

Modeling virtual organizations with Latent Dirichlet Allocation: a case for natural language processing.

PubMed

Gross, Alexander; Murthy, Dhiraj

2014-10-01

This paper explores a variety of methods for applying the Latent Dirichlet Allocation (LDA) automated topic modeling algorithm to the modeling of the structure and behavior of virtual organizations found within modern social media and social networking environments. As the field of Big Data reveals, an increase in the scale of social data available presents new challenges which are not tackled by merely scaling up hardware and software. Rather, they necessitate new methods and, indeed, new areas of expertise. Natural language processing provides one such method. This paper applies LDA to the study of scientific virtual organizations whose members employ social technologies. Because of the vast data footprint in these virtual platforms, we found that natural language processing was needed to 'unlock' and render visible latent, previously unseen conversational connections across large textual corpora (spanning profiles, discussion threads, forums, and other social media incarnations). We introduce variants of LDA and ultimately make the argument that natural language processing is a critical interdisciplinary methodology to make better sense of social 'Big Data' and we were able to successfully model nested discussion topics from forums and blog posts using LDA. Importantly, we found that LDA can move us beyond the state-of-the-art in conventional Social Network Analysis techniques. Copyright © 2014 Elsevier Ltd. All rights reserved.

Classifying free-text triage chief complaints into syndromic categories with natural language processing.

PubMed

Chapman, Wendy W; Christensen, Lee M; Wagner, Michael M; Haug, Peter J; Ivanov, Oleg; Dowling, John N; Olszewski, Robert T

2005-01-01

Develop and evaluate a natural language processing application for classifying chief complaints into syndromic categories for syndromic surveillance. Much of the input data for artificial intelligence applications in the medical field are free-text patient medical records, including dictated medical reports and triage chief complaints. To be useful for automated systems, the free-text must be translated into encoded form. We implemented a biosurveillance detection system from Pennsylvania to monitor the 2002 Winter Olympic Games. Because input data was in free-text format, we used a natural language processing text classifier to automatically classify free-text triage chief complaints into syndromic categories used by the biosurveillance system. The classifier was trained on 4700 chief complaints from Pennsylvania. We evaluated the ability of the classifier to classify free-text chief complaints into syndromic categories with a test set of 800 chief complaints from Utah. The classifier produced the following areas under the ROC curve: Constitutional = 0.95; Gastrointestinal = 0.97; Hemorrhagic = 0.99; Neurological = 0.96; Rash = 1.0; Respiratory = 0.99; Other = 0.96. Using information stored in the system's semantic model, we extracted from the Respiratory classifications lower respiratory complaints and lower respiratory complaints with fever with a precision of 0.97 and 0.96, respectively. Results suggest that a trainable natural language processing text classifier can accurately extract data from free-text chief complaints for biosurveillance.

Second-language instinct and instruction effects: nature and nurture in second-language acquisition.

PubMed

Yusa, Noriaki; Koizumi, Masatoshi; Kim, Jungho; Kimura, Naoki; Uchida, Shinya; Yokoyama, Satoru; Miura, Naoki; Kawashima, Ryuta; Hagiwara, Hiroko

2011-10-01

Adults seem to have greater difficulties than children in acquiring a second language (L2) because of the alleged "window of opportunity" around puberty. Postpuberty Japanese participants learned a new English rule with simplex sentences during one month of instruction, and then they were tested on "uninstructed complex sentences" as well as "instructed simplex sentences." The behavioral data show that they can acquire more knowledge than is instructed, suggesting the interweaving of nature (universal principles of grammar, UG) and nurture (instruction) in L2 acquisition. The comparison in the "uninstructed complex sentences" between post-instruction and pre-instruction using functional magnetic resonance imaging reveals a significant activation in Broca's area. Thus, this study provides new insight into Broca's area, where nature and nurture cooperate to produce L2 learners' rich linguistic knowledge. It also shows neural plasticity of adult L2 acquisition, arguing against a critical period hypothesis, at least in the domain of UG.

Light at Night Markup Language (LANML): XML Technology for Light at Night Monitoring Data

NASA Astrophysics Data System (ADS)

Craine, B. L.; Craine, E. R.; Craine, E. M.; Crawford, D. L.

2013-05-01

Light at Night Markup Language (LANML) is a standard, based upon XML, useful in acquiring, validating, transporting, archiving and analyzing multi-dimensional light at night (LAN) datasets of any size. The LANML standard can accommodate a variety of measurement scenarios including single spot measures, static time-series, web based monitoring networks, mobile measurements, and airborne measurements. LANML is human-readable, machine-readable, and does not require a dedicated parser. In addition LANML is flexible; ensuring future extensions of the format will remain backward compatible with analysis software. The XML technology is at the heart of communicating over the internet and can be equally useful at the desktop level, making this standard particularly attractive for web based applications, educational outreach and efficient collaboration between research groups.

The International English Language Testing System (IELTS): Its Nature and Development.

ERIC Educational Resources Information Center

Ingram, D. E.

The nature and development of the recently released International English Language Testing System (IELTS) instrument are described. The test is the result of a joint Australian-British project to develop a new test for use with foreign students planning to study in English-speaking countries. It is expected that the modular instrument will become…

Quantization, Frobenius and Bi algebras from the Categorical Framework of Quantum Mechanics to Natural Language Semantics

NASA Astrophysics Data System (ADS)

Sadrzadeh, Mehrnoosh

2017-07-01

Compact Closed categories and Frobenius and Bi algebras have been applied to model and reason about Quantum protocols. The same constructions have also been applied to reason about natural language semantics under the name: ``categorical distributional compositional'' semantics, or in short, the ``DisCoCat'' model. This model combines the statistical vector models of word meaning with the compositional models of grammatical structure. It has been applied to natural language tasks such as disambiguation, paraphrasing and entailment of phrases and sentences. The passage from the grammatical structure to vectors is provided by a functor, similar to the Quantization functor of Quantum Field Theory. The original DisCoCat model only used compact closed categories. Later, Frobenius algebras were added to it to model long distance dependancies such as relative pronouns. Recently, bialgebras have been added to the pack to reason about quantifiers. This paper reviews these constructions and their application to natural language semantics. We go over the theory and present some of the core experimental results.

NLPIR: A Theoretical Framework for Applying Natural Language Processing to Information Retrieval.

ERIC Educational Resources Information Center

Zhou, Lina; Zhang, Dongsong

2003-01-01

Proposes a theoretical framework called NLPIR that integrates natural language processing (NLP) into information retrieval (IR) based on the assumption that there exists representation distance between queries and documents. Discusses problems in traditional keyword-based IR, including relevance, and describes some existing NLP techniques.…

Language and Interactional Discourse: Deconstrusting the Talk-Generating Machinery in Natural Conversation

ERIC Educational Resources Information Center

Enyi, Amaechi Uneke

2015-01-01

The study entitled "Language and Interactional Discourse: Deconstructing the Talk-Generating Machinery in Natural Conversation" is an analysis of spontaneous and informal conversation. The study, carried out in the theoretical and methodological tradition of Ethnomethodology, was aimed at explicating how ordinary talk is organized and…

The application of natural language processing to augmentative and alternative communication.

PubMed

Higginbotham, D Jeffery; Lesher, Gregory W; Moulton, Bryan J; Roark, Brian

2011-01-01

Significant progress has been made in the application of natural language processing (NLP) to augmentative and alternative communication (AAC), particularly in the areas of interface design and word prediction. This article will survey the current state-of-the-science of NLP in AAC and discuss its future applications for the development of next generation of AAC technology.

A Qualitative Analysis Framework Using Natural Language Processing and Graph Theory

ERIC Educational Resources Information Center

Tierney, Patrick J.

2012-01-01

This paper introduces a method of extending natural language-based processing of qualitative data analysis with the use of a very quantitative tool--graph theory. It is not an attempt to convert qualitative research to a positivist approach with a mathematical black box, nor is it a "graphical solution". Rather, it is a method to help qualitative…

BIT BY BIT: A Game Simulating Natural Language Processing in Computers

ERIC Educational Resources Information Center

Kato, Taichi; Arakawa, Chuichi

2008-01-01

BIT BY BIT is an encryption game that is designed to improve students' understanding of natural language processing in computers. Participants encode clear words into binary code using an encryption key and exchange them in the game. BIT BY BIT enables participants who do not understand the concept of binary numbers to perform the process of…

The Linguistic Correlates of Conversational Deception: Comparing Natural Language Processing Technologies

ERIC Educational Resources Information Center

Duran, Nicholas D.; Hall, Charles; McCarthy, Philip M.; McNamara, Danielle S.

2010-01-01

The words people use and the way they use them can reveal a great deal about their mental states when they attempt to deceive. The challenge for researchers is how to reliably distinguish the linguistic features that characterize these hidden states. In this study, we use a natural language processing tool called Coh-Metrix to evaluate deceptive…

Combining Machine Learning and Natural Language Processing to Assess Literary Text Comprehension

ERIC Educational Resources Information Center

Balyan, Renu; McCarthy, Kathryn S.; McNamara, Danielle S.

2017-01-01

This study examined how machine learning and natural language processing (NLP) techniques can be leveraged to assess the interpretive behavior that is required for successful literary text comprehension. We compared the accuracy of seven different machine learning classification algorithms in predicting human ratings of student essays about…

Visual statistical learning is related to natural language ability in adults: An ERP Study

PubMed Central

Daltrozzo, Jerome; Emerson, Samantha N.; Deocampo, Joanne; Singh, Sonia; Freggens, Marjorie; Branum-Martin, Lee; Conway, Christopher M.

2017-01-01

Statistical learning (SL) is believed to enable language acquisition by allowing individuals to learn regularities within linguistic input. However, neural evidence supporting a direct relationship between SL and language ability is scarce. We investigated whether there are associations between event-related potential (ERP) correlates of SL and language abilities while controlling for the general level of selective attention. Seventeen adults completed tests of visual SL, receptive vocabulary, grammatical ability, and sentence completion. Response times and ERPs showed that SL is related to receptive vocabulary and grammatical ability. ERPs indicated that the relationship between SL and grammatical ability was independent of attention while the association between SL and receptive vocabulary depended on attention. The implications of these dissociative relationships in terms of underlying mechanisms of SL and language are discussed. These results further elucidate the cognitive nature of the links between SL mechanisms and language abilities. PMID:28086142

Using Edit Distance to Analyse Errors in a Natural Language to Logic Translation Corpus

ERIC Educational Resources Information Center

Barker-Plummer, Dave; Dale, Robert; Cox, Richard; Romanczuk, Alex

2012-01-01

We have assembled a large corpus of student submissions to an automatic grading system, where the subject matter involves the translation of natural language sentences into propositional logic. Of the 2.3 million translation instances in the corpus, 286,000 (approximately 12%) are categorized as being in error. We want to understand the nature of…

Voice-Dictated versus Typed-in Clinician Notes: Linguistic Properties and the Potential Implications on Natural Language Processing

PubMed Central

Zheng, Kai; Mei, Qiaozhu; Yang, Lei; Manion, Frank J.; Balis, Ulysses J.; Hanauer, David A.

2011-01-01

In this study, we comparatively examined the linguistic properties of narrative clinician notes created through voice dictation versus those directly entered by clinicians via a computer keyboard. Intuitively, the nature of voice-dictated notes would resemble that of natural language, while typed-in notes may demonstrate distinctive language features for reasons such as intensive usage of acronyms. The study analyses were based on an empirical dataset retrieved from our institutional electronic health records system. The dataset contains 30,000 voice-dictated notes and 30,000 notes that were entered manually; both were encounter notes generated in ambulatory care settings. The results suggest that between the narrative clinician notes created via these two different methods, there exists a considerable amount of lexical and distributional differences. Such differences could have a significant impact on the performance of natural language processing tools, necessitating these two different types of documents being differentially treated. PMID:22195229

Inter-Annotator Agreement and the Upper Limit on Machine Performance: Evidence from Biomedical Natural Language Processing.

PubMed

Boguslav, Mayla; Cohen, Kevin Bretonnel

2017-01-01

Human-annotated data is a fundamental part of natural language processing system development and evaluation. The quality of that data is typically assessed by calculating the agreement between the annotators. It is widely assumed that this agreement between annotators is the upper limit on system performance in natural language processing: if humans can't agree with each other about the classification more than some percentage of the time, we don't expect a computer to do any better. We trace the logical positivist roots of the motivation for measuring inter-annotator agreement, demonstrate the prevalence of the widely-held assumption about the relationship between inter-annotator agreement and system performance, and present data that suggest that inter-annotator agreement is not, in fact, an upper bound on language processing system performance.

A Tutorial on Techniques and Applications for Natural Language Processing

DTIC Science & Technology

1983-10-17

mentioned above as specific to context-free grammars were tackled by linguists, in particular Chomsky [21, 221 through Transformational Grammar . As shown...DTIC e, C 17 October 1983 MAY 1,5 1990 DEPARTMENT of COMPUTER SCIENCE Approved for pu ]3 -- ,. " Carnegie-Mellon University . . . - -A.,,Anm m n n n n ln...A Tutorial on Techniques and Applications for Natural Language Processing Philip J. Hayes and Jaime G. Carbonell Carnegie-Mellon University 17

Toward a Theory-Based Natural Language Capability in Robots and Other Embodied Agents: Evaluating Hausser's SLIM Theory and Database Semantics

ERIC Educational Resources Information Center

Burk, Robin K.

2010-01-01

Computational natural language understanding and generation have been a goal of artificial intelligence since McCarthy, Minsky, Rochester and Shannon first proposed to spend the summer of 1956 studying this and related problems. Although statistical approaches dominate current natural language applications, two current research trends bring…

Visual statistical learning is related to natural language ability in adults: An ERP study.

PubMed

Daltrozzo, Jerome; Emerson, Samantha N; Deocampo, Joanne; Singh, Sonia; Freggens, Marjorie; Branum-Martin, Lee; Conway, Christopher M

2017-03-01

Statistical learning (SL) is believed to enable language acquisition by allowing individuals to learn regularities within linguistic input. However, neural evidence supporting a direct relationship between SL and language ability is scarce. We investigated whether there are associations between event-related potential (ERP) correlates of SL and language abilities while controlling for the general level of selective attention. Seventeen adults completed tests of visual SL, receptive vocabulary, grammatical ability, and sentence completion. Response times and ERPs showed that SL is related to receptive vocabulary and grammatical ability. ERPs indicated that the relationship between SL and grammatical ability was independent of attention while the association between SL and receptive vocabulary depended on attention. The implications of these dissociative relationships in terms of underlying mechanisms of SL and language are discussed. These results further elucidate the cognitive nature of the links between SL mechanisms and language abilities. Copyright © 2017 Elsevier Inc. All rights reserved.

Comparative study on the customization of natural language interfaces to databases.

PubMed

Pazos R, Rodolfo A; Aguirre L, Marco A; González B, Juan J; Martínez F, José A; Pérez O, Joaquín; Verástegui O, Andrés A

2016-01-01

In the last decades the popularity of natural language interfaces to databases (NLIDBs) has increased, because in many cases information obtained from them is used for making important business decisions. Unfortunately, the complexity of their customization by database administrators make them difficult to use. In order for a NLIDB to obtain a high percentage of correctly translated queries, it is necessary that it is correctly customized for the database to be queried. In most cases the performance reported in NLIDB literature is the highest possible; i.e., the performance obtained when the interfaces were customized by the implementers. However, for end users it is more important the performance that the interface can yield when the NLIDB is customized by someone different from the implementers. Unfortunately, there exist very few articles that report NLIDB performance when the NLIDBs are not customized by the implementers. This article presents a semantically-enriched data dictionary (which permits solving many of the problems that occur when translating from natural language to SQL) and an experiment in which two groups of undergraduate students customized our NLIDB and English language frontend (ELF), considered one of the best available commercial NLIDBs. The experimental results show that, when customized by the first group, our NLIDB obtained a 44.69 % of correctly answered queries and ELF 11.83 % for the ATIS database, and when customized by the second group, our NLIDB attained 77.05 % and ELF 13.48 %. The performance attained by our NLIDB, when customized by ourselves was 90 %.

Linking sounds to meanings: infant statistical learning in a natural language.

PubMed

Hay, Jessica F; Pelucchi, Bruna; Graf Estes, Katharine; Saffran, Jenny R

2011-09-01

The processes of infant word segmentation and infant word learning have largely been studied separately. However, the ease with which potential word forms are segmented from fluent speech seems likely to influence subsequent mappings between words and their referents. To explore this process, we tested the link between the statistical coherence of sequences presented in fluent speech and infants' subsequent use of those sequences as labels for novel objects. Notably, the materials were drawn from a natural language unfamiliar to the infants (Italian). The results of three experiments suggest that there is a close relationship between the statistics of the speech stream and subsequent mapping of labels to referents. Mapping was facilitated when the labels contained high transitional probabilities in the forward and/or backward direction (Experiment 1). When no transitional probability information was available (Experiment 2), or when the internal transitional probabilities of the labels were low in both directions (Experiment 3), infants failed to link the labels to their referents. Word learning appears to be strongly influenced by infants' prior experience with the distribution of sounds that make up words in natural languages. Copyright © 2011 Elsevier Inc. All rights reserved.

Speech perception and reading: two parallel modes of understanding language and implications for acquiring literacy naturally.

PubMed

Massaro, Dominic W

2012-01-01

I review 2 seminal research reports published in this journal during its second decade more than a century ago. Given psychology's subdisciplines, they would not normally be reviewed together because one involves reading and the other speech perception. The small amount of interaction between these domains might have limited research and theoretical progress. In fact, the 2 early research reports revealed common processes involved in these 2 forms of language processing. Their illustration of the role of Wundt's apperceptive process in reading and speech perception anticipated descriptions of contemporary theories of pattern recognition, such as the fuzzy logical model of perception. Based on the commonalities between reading and listening, one can question why they have been viewed so differently. It is commonly believed that learning to read requires formal instruction and schooling, whereas spoken language is acquired from birth onward through natural interactions with people who talk. Most researchers and educators believe that spoken language is acquired naturally from birth onward and even prenatally. Learning to read, on the other hand, is not possible until the child has acquired spoken language, reaches school age, and receives formal instruction. If an appropriate form of written text is made available early in a child's life, however, the current hypothesis is that reading will also be learned inductively and emerge naturally, with no significant negative consequences. If this proposal is true, it should soon be possible to create an interactive system, Technology Assisted Reading Acquisition, to allow children to acquire literacy naturally.

Natural language processing-based COTS software and related technologies survey.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stickland, Michael G.; Conrad, Gregory N.; Eaton, Shelley M.

Natural language processing-based knowledge management software, traditionally developed for security organizations, is now becoming commercially available. An informal survey was conducted to discover and examine current NLP and related technologies and potential applications for information retrieval, information extraction, summarization, categorization, terminology management, link analysis, and visualization for possible implementation at Sandia National Laboratories. This report documents our current understanding of the technologies, lists software vendors and their products, and identifies potential applications of these technologies.

Human task animation from performance models and natural language input

NASA Technical Reports Server (NTRS)

Esakov, Jeffrey; Badler, Norman I.; Jung, Moon

1989-01-01

Graphical manipulation of human figures is essential for certain types of human factors analyses such as reach, clearance, fit, and view. In many situations, however, the animation of simulated people performing various tasks may be based on more complicated functions involving multiple simultaneous reaches, critical timing, resource availability, and human performance capabilities. One rather effective means for creating such a simulation is through a natural language description of the tasks to be carried out. Given an anthropometrically-sized figure and a geometric workplace environment, various simple actions such as reach, turn, and view can be effectively controlled from language commands or standard NASA checklist procedures. The commands may also be generated by external simulation tools. Task timing is determined from actual performance models, if available, such as strength models or Fitts' Law. The resulting action specification are animated on a Silicon Graphics Iris workstation in real-time.

Computer Applications in Professional Writing: Systems that Analyze and Describe Natural Language.

ERIC Educational Resources Information Center

O'Brien, Frank

Two varieties of user-friendly computer systems that deal with natural language are now available, providing either at-the-monitor stylistic and grammatic correction of keyed-in writing or a sorting, selecting, and generating of statistical data for any written or spoken document. The editor programs, such as "The Writer's Workbench"…

Teaching the Tacit Knowledge of Programming to Novices with Natural Language Tutoring

ERIC Educational Resources Information Center

Lane, H. Chad; VanLehn, Kurt

2005-01-01

For beginning programmers, inadequate problem solving and planning skills are among the most salient of their weaknesses. In this paper, we test the efficacy of natural language tutoring to teach and scaffold acquisition of these skills. We describe ProPL (Pro-PELL), a dialogue-based intelligent tutoring system that elicits goal decompositions and…

Modeling Coevolution between Language and Memory Capacity during Language Origin

PubMed Central

Gong, Tao; Shuai, Lan

2015-01-01

Memory is essential to many cognitive tasks including language. Apart from empirical studies of memory effects on language acquisition and use, there lack sufficient evolutionary explorations on whether a high level of memory capacity is prerequisite for language and whether language origin could influence memory capacity. In line with evolutionary theories that natural selection refined language-related cognitive abilities, we advocated a coevolution scenario between language and memory capacity, which incorporated the genetic transmission of individual memory capacity, cultural transmission of idiolects, and natural and cultural selections on individual reproduction and language teaching. To illustrate the coevolution dynamics, we adopted a multi-agent computational model simulating the emergence of lexical items and simple syntax through iterated communications. Simulations showed that: along with the origin of a communal language, an initially-low memory capacity for acquired linguistic knowledge was boosted; and such coherent increase in linguistic understandability and memory capacities reflected a language-memory coevolution; and such coevolution stopped till memory capacities became sufficient for language communications. Statistical analyses revealed that the coevolution was realized mainly by natural selection based on individual communicative success in cultural transmissions. This work elaborated the biology-culture parallelism of language evolution, demonstrated the driving force of culturally-constituted factors for natural selection of individual cognitive abilities, and suggested that the degree difference in language-related cognitive abilities between humans and nonhuman animals could result from a coevolution with language. PMID:26544876

Modeling Coevolution between Language and Memory Capacity during Language Origin.

PubMed

Gong, Tao; Shuai, Lan

2015-01-01

Memory is essential to many cognitive tasks including language. Apart from empirical studies of memory effects on language acquisition and use, there lack sufficient evolutionary explorations on whether a high level of memory capacity is prerequisite for language and whether language origin could influence memory capacity. In line with evolutionary theories that natural selection refined language-related cognitive abilities, we advocated a coevolution scenario between language and memory capacity, which incorporated the genetic transmission of individual memory capacity, cultural transmission of idiolects, and natural and cultural selections on individual reproduction and language teaching. To illustrate the coevolution dynamics, we adopted a multi-agent computational model simulating the emergence of lexical items and simple syntax through iterated communications. Simulations showed that: along with the origin of a communal language, an initially-low memory capacity for acquired linguistic knowledge was boosted; and such coherent increase in linguistic understandability and memory capacities reflected a language-memory coevolution; and such coevolution stopped till memory capacities became sufficient for language communications. Statistical analyses revealed that the coevolution was realized mainly by natural selection based on individual communicative success in cultural transmissions. This work elaborated the biology-culture parallelism of language evolution, demonstrated the driving force of culturally-constituted factors for natural selection of individual cognitive abilities, and suggested that the degree difference in language-related cognitive abilities between humans and nonhuman animals could result from a coevolution with language.

Language related differences of the sustained response evoked by natural speech sounds.

PubMed

Fan, Christina Siu-Dschu; Zhu, Xingyu; Dosch, Hans Günter; von Stutterheim, Christiane; Rupp, André

2017-01-01

In tonal languages, such as Mandarin Chinese, the pitch contour of vowels discriminates lexical meaning, which is not the case in non-tonal languages such as German. Recent data provide evidence that pitch processing is influenced by language experience. However, there are still many open questions concerning the representation of such phonological and language-related differences at the level of the auditory cortex (AC). Using magnetoencephalography (MEG), we recorded transient and sustained auditory evoked fields (AEF) in native Chinese and German speakers to investigate language related phonological and semantic aspects in the processing of acoustic stimuli. AEF were elicited by spoken meaningful and meaningless syllables, by vowels, and by a French horn tone. Speech sounds were recorded from a native speaker and showed frequency-modulations according to the pitch-contours of Mandarin. The sustained field (SF) evoked by natural speech signals was significantly larger for Chinese than for German listeners. In contrast, the SF elicited by a horn tone was not significantly different between groups. Furthermore, the SF of Chinese subjects was larger when evoked by meaningful syllables compared to meaningless ones, but there was no significant difference regarding whether vowels were part of the Chinese phonological system or not. Moreover, the N100m gave subtle but clear evidence that for Chinese listeners other factors than purely physical properties play a role in processing meaningful signals. These findings show that the N100 and the SF generated in Heschl's gyrus are influenced by language experience, which suggests that AC activity related to specific pitch contours of vowels is influenced in a top-down fashion by higher, language related areas. Such interactions are in line with anatomical findings and neuroimaging data, as well as with the dual-stream model of language of Hickok and Poeppel that highlights the close and reciprocal interaction between

Using Open Geographic Data to Generate Natural Language Descriptions for Hydrological Sensor Networks.

PubMed

Molina, Martin; Sanchez-Soriano, Javier; Corcho, Oscar

2015-07-03

Providing descriptions of isolated sensors and sensor networks in natural language, understandable by the general public, is useful to help users find relevant sensors and analyze sensor data. In this paper, we discuss the feasibility of using geographic knowledge from public databases available on the Web (such as OpenStreetMap, Geonames, or DBpedia) to automatically construct such descriptions. We present a general method that uses such information to generate sensor descriptions in natural language. The results of the evaluation of our method in a hydrologic national sensor network showed that this approach is feasible and capable of generating adequate sensor descriptions with a lower development effort compared to other approaches. In the paper we also analyze certain problems that we found in public databases (e.g., heterogeneity, non-standard use of labels, or rigid search methods) and their impact in the generation of sensor descriptions.

Using Open Geographic Data to Generate Natural Language Descriptions for Hydrological Sensor Networks

PubMed Central

Molina, Martin; Sanchez-Soriano, Javier; Corcho, Oscar

2015-01-01

Providing descriptions of isolated sensors and sensor networks in natural language, understandable by the general public, is useful to help users find relevant sensors and analyze sensor data. In this paper, we discuss the feasibility of using geographic knowledge from public databases available on the Web (such as OpenStreetMap, Geonames, or DBpedia) to automatically construct such descriptions. We present a general method that uses such information to generate sensor descriptions in natural language. The results of the evaluation of our method in a hydrologic national sensor network showed that this approach is feasible and capable of generating adequate sensor descriptions with a lower development effort compared to other approaches. In the paper we also analyze certain problems that we found in public databases (e.g., heterogeneity, non-standard use of labels, or rigid search methods) and their impact in the generation of sensor descriptions. PMID:26151211

Harnessing Biomedical Natural Language Processing Tools to Identify Medicinal Plant Knowledge from Historical Texts.

PubMed

Sharma, Vivekanand; Law, Wayne; Balick, Michael J; Sarkar, Indra Neil

2017-01-01

The growing amount of data describing historical medicinal uses of plants from digitization efforts provides the opportunity to develop systematic approaches for identifying potential plant-based therapies. However, the task of cataloguing plant use information from natural language text is a challenging task for ethnobotanists. To date, there have been only limited adoption of informatics approaches used for supporting the identification of ethnobotanical information associated with medicinal uses. This study explored the feasibility of using biomedical terminologies and natural language processing approaches for extracting relevant plant-associated therapeutic use information from historical biodiversity literature collection available from the Biodiversity Heritage Library. The results from this preliminary study suggest that there is potential utility of informatics methods to identify medicinal plant knowledge from digitized resources as well as highlight opportunities for improvement.

Harnessing Biomedical Natural Language Processing Tools to Identify Medicinal Plant Knowledge from Historical Texts

PubMed Central

Sharma, Vivekanand; Law, Wayne; Balick, Michael J.; Sarkar, Indra Neil

2017-01-01

The growing amount of data describing historical medicinal uses of plants from digitization efforts provides the opportunity to develop systematic approaches for identifying potential plant-based therapies. However, the task of cataloguing plant use information from natural language text is a challenging task for ethnobotanists. To date, there have been only limited adoption of informatics approaches used for supporting the identification of ethnobotanical information associated with medicinal uses. This study explored the feasibility of using biomedical terminologies and natural language processing approaches for extracting relevant plant-associated therapeutic use information from historical biodiversity literature collection available from the Biodiversity Heritage Library. The results from this preliminary study suggest that there is potential utility of informatics methods to identify medicinal plant knowledge from digitized resources as well as highlight opportunities for improvement. PMID:29854223

A Cognitive Neural Architecture Able to Learn and Communicate through Natural Language.

PubMed

Golosio, Bruno; Cangelosi, Angelo; Gamotina, Olesya; Masala, Giovanni Luca

2015-01-01

Communicative interactions involve a kind of procedural knowledge that is used by the human brain for processing verbal and nonverbal inputs and for language production. Although considerable work has been done on modeling human language abilities, it has been difficult to bring them together to a comprehensive tabula rasa system compatible with current knowledge of how verbal information is processed in the brain. This work presents a cognitive system, entirely based on a large-scale neural architecture, which was developed to shed light on the procedural knowledge involved in language elaboration. The main component of this system is the central executive, which is a supervising system that coordinates the other components of the working memory. In our model, the central executive is a neural network that takes as input the neural activation states of the short-term memory and yields as output mental actions, which control the flow of information among the working memory components through neural gating mechanisms. The proposed system is capable of learning to communicate through natural language starting from tabula rasa, without any a priori knowledge of the structure of phrases, meaning of words, role of the different classes of words, only by interacting with a human through a text-based interface, using an open-ended incremental learning process. It is able to learn nouns, verbs, adjectives, pronouns and other word classes, and to use them in expressive language. The model was validated on a corpus of 1587 input sentences, based on literature on early language assessment, at the level of about 4-years old child, and produced 521 output sentences, expressing a broad range of language processing functionalities.

Evaluating a normalized conceptual representation produced from natural language patient discharge summaries.

PubMed Central

Zweigenbaum, P.; Bouaud, J.; Bachimont, B.; Charlet, J.; Boisvieux, J. F.

1997-01-01

The Menelas project aimed to produce a normalized conceptual representation from natural language patient discharge summaries. Because of the complex and detailed nature of conceptual representations, evaluating the quality of output of such a system is difficult. We present the method designed to measure the quality of Menelas output, and its application to the state of the French Menelas prototype as of the end of the project. We examine this method in the framework recently proposed by Friedman and Hripcsak. We also propose two conditions which enable to reduce the evaluation preparation workload. PMID:9357694

Tasking and sharing sensing assets using controlled natural language

NASA Astrophysics Data System (ADS)

Preece, Alun; Pizzocaro, Diego; Braines, David; Mott, David

2012-06-01

We introduce an approach to representing intelligence, surveillance, and reconnaissance (ISR) tasks at a relatively high level in controlled natural language. We demonstrate that this facilitates both human interpretation and machine processing of tasks. More specically, it allows the automatic assignment of sensing assets to tasks, and the informed sharing of tasks between collaborating users in a coalition environment. To enable automatic matching of sensor types to tasks, we created a machine-processable knowledge representation based on the Military Missions and Means Framework (MMF), and implemented a semantic reasoner to match task types to sensor types. We combined this mechanism with a sensor-task assignment procedure based on a well-known distributed protocol for resource allocation. In this paper, we re-formulate the MMF ontology in Controlled English (CE), a type of controlled natural language designed to be readable by a native English speaker whilst representing information in a structured, unambiguous form to facilitate machine processing. We show how CE can be used to describe both ISR tasks (for example, detection, localization, or identication of particular kinds of object) and sensing assets (for example, acoustic, visual, or seismic sensors, mounted on motes or unmanned vehicles). We show how these representations enable an automatic sensor-task assignment process. Where a group of users are cooperating in a coalition, we show how CE task summaries give users in the eld a high-level picture of ISR coverage of an area of interest. This allows them to make ecient use of sensing resources by sharing tasks.

NLPReViz: an interactive tool for natural language processing on clinical text.

PubMed

Trivedi, Gaurav; Pham, Phuong; Chapman, Wendy W; Hwa, Rebecca; Wiebe, Janyce; Hochheiser, Harry

2018-01-01

The gap between domain experts and natural language processing expertise is a barrier to extracting understanding from clinical text. We describe a prototype tool for interactive review and revision of natural language processing models of binary concepts extracted from clinical notes. We evaluated our prototype in a user study involving 9 physicians, who used our tool to build and revise models for 2 colonoscopy quality variables. We report changes in performance relative to the quantity of feedback. Using initial training sets as small as 10 documents, expert review led to final F1scores for the "appendiceal-orifice" variable between 0.78 and 0.91 (with improvements ranging from 13.26% to 29.90%). F1for "biopsy" ranged between 0.88 and 0.94 (-1.52% to 11.74% improvements). The average System Usability Scale score was 70.56. Subjective feedback also suggests possible design improvements. © The Author 2017. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

An intelligent tutoring system that generates a natural language dialogue using dynamic multi-level planning.

PubMed

Woo, Chong Woo; Evens, Martha W; Freedman, Reva; Glass, Michael; Shim, Leem Seop; Zhang, Yuemei; Zhou, Yujian; Michael, Joel

2006-09-01

The objective of this research was to build an intelligent tutoring system capable of carrying on a natural language dialogue with a student who is solving a problem in physiology. Previous experiments have shown that students need practice in qualitative causal reasoning to internalize new knowledge and to apply it effectively and that they learn by putting their ideas into words. Analysis of a corpus of 75 hour-long tutoring sessions carried on in keyboard-to-keyboard style by two professors of physiology at Rush Medical College tutoring first-year medical students provided the rules used in tutoring strategies and tactics, parsing, and text generation. The system presents the student with a perturbation to the blood pressure, asks for qualitative predictions of the changes produced in seven important cardiovascular variables, and then launches a dialogue to correct any errors and to probe for possible misconceptions. The natural language understanding component uses a cascade of finite-state machines. The generation is based on lexical functional grammar. Results of experiments with pretests and posttests have shown that using the system for an hour produces significant learning gains and also that even this brief use improves the student's ability to solve problems more then reading textual material on the topic. Student surveys tell us that students like the system and feel that they learn from it. The system is now in regular use in the first-year physiology course at Rush Medical College. We conclude that the CIRCSIM-Tutor system demonstrates that intelligent tutoring systems can implement effective natural language dialogue with current language technology.

Predicting complex syntactic structure in real time: Processing of negative sentences in Russian.

PubMed

Kazanina, Nina

2017-11-01

In Russian negative sentences the verb's direct object may appear either in the accusative case, which is licensed by the verb (as is common cross-linguistically), or in the genitive case, which is licensed by the negation (Russian-specific "genitive-of-negation" phenomenon). Such sentences were used to investigate whether case marking is employed for anticipating syntactic structure, and whether lexical heads other than the verb can be predicted on the basis of a case-marked noun phrase. Experiment 1, a completion task, confirmed that genitive-of-negation is part of Russian speakers' active grammatical repertoire. In Experiments 2 and 3, the genitive/accusative case manipulation on the preverbal object led to shorter reading times at the negation and verb in the genitive versus accusative condition. Furthermore, Experiment 3 manipulated linear order of the direct object and the negated verb in order to distinguish whether the abovementioned facilitatory effect was predictive or integrative in nature, and concluded that the parser actively predicts a verb and (otherwise optional) negation on the basis of a preceding genitive-marked object. Similarly to a head-final language, case-marking information on preverbal noun phrases (NPs) is used by the parser to enable incremental structure building in a free-word-order language such as Russian.

Clinician-Oriented Access to Data - C.O.A.D.: A Natural Language Interface to a VA DHCP Database

PubMed Central

Levy, Christine; Rogers, Elizabeth

1995-01-01

Hospitals collect enormous amounts of data related to the on-going care of patients. Unfortunately, a clinicians access to the data is limited by complexities of the database structure and/or programming skills required to access the database. The COAD project attempts to bridge the gap between the clinical user's need for specific information from the database, and the wealth of data residing in the hospital information system. The project design includes a natural language interface to data contained in a VA DHCP database. We have developed a prototype which links natural language software to certain DHCP data elements, including, patient demographics, prescriptions, diagnoses, laboratory data, and provider information. English queries can by typed onto the system, and answers to the questions are returned. Future work includes refinement of natural language/DHCP connections to enable more sophisticated queries, and optimization of the system to reduce response time to user questions.

Natural language processing pipelines to annotate BioC collections with an application to the NCBI disease corpus

PubMed Central

Comeau, Donald C.; Liu, Haibin; Islamaj Doğan, Rezarta; Wilbur, W. John

2014-01-01

BioC is a new format and associated code libraries for sharing text and annotations. We have implemented BioC natural language preprocessing pipelines in two popular programming languages: C++ and Java. The current implementations interface with the well-known MedPost and Stanford natural language processing tool sets. The pipeline functionality includes sentence segmentation, tokenization, part-of-speech tagging, lemmatization and sentence parsing. These pipelines can be easily integrated along with other BioC programs into any BioC compliant text mining systems. As an application, we converted the NCBI disease corpus to BioC format, and the pipelines have successfully run on this corpus to demonstrate their functionality. Code and data can be downloaded from http://bioc.sourceforge.net. Database URL: http://bioc.sourceforge.net PMID:24935050

Assistance and Feedback Mechanism in an Intelligent Tutoring System for Teaching Conversion of Natural Language into Logic

ERIC Educational Resources Information Center

Perikos, Isidoros; Grivokostopoulou, Foteini; Hatzilygeroudis, Ioannis

2017-01-01

Logic as a knowledge representation and reasoning language is a fundamental topic of an Artificial Intelligence (AI) course and includes a number of sub-topics. One of them, which brings difficulties to students to deal with, is converting natural language (NL) sentences into first-order logic (FOL) formulas. To assist students to overcome those…

Research and Development in Natural Language Understanding as Part of the Strategic Computing Program.

DTIC Science & Technology

1987-04-01

facilities. BBN is developing a series of increasingly sophisticated natural language understanding systems which will serve as an integrated interface...Haas, A.R. A Syntactic Theory of Belief and Action. Artificial Intelligence. 1986. Forthcoming. [6] Hinrichs, E. Temporale Anaphora im Englischen

Language Revitalization.

ERIC Educational Resources Information Center

Hinton, Leanne

2003-01-01

Surveys developments in language revitalization and language death. Focusing on indigenous languages, discusses the role and nature of appropriate linguistic documentation, possibilities for bilingual education, and methods of promoting oral fluency and intergenerational transmission in affected languages. (Author/VWL)

Laboratory process control using natural language commands from a personal computer

NASA Technical Reports Server (NTRS)

Will, Herbert A.; Mackin, Michael A.

1989-01-01

PC software is described which provides flexible natural language process control capability with an IBM PC or compatible machine. Hardware requirements include the PC, and suitable hardware interfaces to all controlled devices. Software required includes the Microsoft Disk Operating System (MS-DOS) operating system, a PC-based FORTRAN-77 compiler, and user-written device drivers. Instructions for use of the software are given as well as a description of an application of the system.

Spatial and numerical abilities without a complete natural language.

PubMed

Hyde, Daniel C; Winkler-Rhoades, Nathan; Lee, Sang-Ah; Izard, Veronique; Shapiro, Kevin A; Spelke, Elizabeth S

2011-04-01

We studied the cognitive abilities of a 13-year-old deaf child, deprived of most linguistic input from late infancy, in a battery of tests designed to reveal the nature of numerical and geometrical abilities in the absence of a full linguistic system. Tests revealed widespread proficiency in basic symbolic and non-symbolic numerical computations involving the use of both exact and approximate numbers. Tests of spatial and geometrical abilities revealed an interesting patchwork of age-typical strengths and localized deficits. In particular, the child performed extremely well on navigation tasks involving geometrical or landmark information presented in isolation, but very poorly on otherwise similar tasks that required the combination of the two types of spatial information. Tests of number- and space-specific language revealed proficiency in the use of number words and deficits in the use of spatial terms. This case suggests that a full linguistic system is not necessary to reap the benefits of linguistic vocabulary on basic numerical tasks. Furthermore, it suggests that language plays an important role in the combination of mental representations of space. Copyright © 2010 Elsevier Ltd. All rights reserved.

Natural language processing pipelines to annotate BioC collections with an application to the NCBI disease corpus.

PubMed

Comeau, Donald C; Liu, Haibin; Islamaj Doğan, Rezarta; Wilbur, W John

2014-01-01

BioC is a new format and associated code libraries for sharing text and annotations. We have implemented BioC natural language preprocessing pipelines in two popular programming languages: C++ and Java. The current implementations interface with the well-known MedPost and Stanford natural language processing tool sets. The pipeline functionality includes sentence segmentation, tokenization, part-of-speech tagging, lemmatization and sentence parsing. These pipelines can be easily integrated along with other BioC programs into any BioC compliant text mining systems. As an application, we converted the NCBI disease corpus to BioC format, and the pipelines have successfully run on this corpus to demonstrate their functionality. Code and data can be downloaded from http://bioc.sourceforge.net. Database URL: http://bioc.sourceforge.net. © The Author(s) 2014. Published by Oxford University Press.

You Are Your Words: Modeling Students' Vocabulary Knowledge with Natural Language Processing Tools

ERIC Educational Resources Information Center

Allen, Laura K.; McNamara, Danielle S.

2015-01-01

The current study investigates the degree to which the lexical properties of students' essays can inform stealth assessments of their vocabulary knowledge. In particular, we used indices calculated with the natural language processing tool, TAALES, to predict students' performance on a measure of vocabulary knowledge. To this end, two corpora were…

Steering the conversation: A linguistic exploration of natural language interactions with a digital assistant during simulated driving.

PubMed

Large, David R; Clark, Leigh; Quandt, Annie; Burnett, Gary; Skrypchuk, Lee

2017-09-01

Given the proliferation of 'intelligent' and 'socially-aware' digital assistants embodying everyday mobile technology - and the undeniable logic that utilising voice-activated controls and interfaces in cars reduces the visual and manual distraction of interacting with in-vehicle devices - it appears inevitable that next generation vehicles will be embodied by digital assistants and utilise spoken language as a method of interaction. From a design perspective, defining the language and interaction style that a digital driving assistant should adopt is contingent on the role that they play within the social fabric and context in which they are situated. We therefore conducted a qualitative, Wizard-of-Oz study to explore how drivers might interact linguistically with a natural language digital driving assistant. Twenty-five participants drove for 10 min in a medium-fidelity driving simulator while interacting with a state-of-the-art, high-functioning, conversational digital driving assistant. All exchanges were transcribed and analysed using recognised linguistic techniques, such as discourse and conversation analysis, normally reserved for interpersonal investigation. Language usage patterns demonstrate that interactions with the digital assistant were fundamentally social in nature, with participants affording the assistant equal social status and high-level cognitive processing capability. For example, participants were polite, actively controlled turn-taking during the conversation, and used back-channelling, fillers and hesitation, as they might in human communication. Furthermore, participants expected the digital assistant to understand and process complex requests mitigated with hedging words and expressions, and peppered with vague language and deictic references requiring shared contextual information and mutual understanding. Findings are presented in six themes which emerged during the analysis - formulating responses; turn-taking; back

Deviations in the Zipf and Heaps laws in natural languages

NASA Astrophysics Data System (ADS)

Bochkarev, Vladimir V.; Lerner, Eduard Yu; Shevlyakova, Anna V.

2014-03-01

This paper is devoted to verifying of the empirical Zipf and Hips laws in natural languages using Google Books Ngram corpus data. The connection between the Zipf and Heaps law which predicts the power dependence of the vocabulary size on the text size is discussed. In fact, the Heaps exponent in this dependence varies with the increasing of the text corpus. To explain it, the obtained results are compared with the probability model of text generation. Quasi-periodic variations with characteristic time periods of 60-100 years were also found.

Revealing the Naturalization of Language and Literacy: The Common Sense of Text Complexity

ERIC Educational Resources Information Center

Newhouse, Erica H.

2017-01-01

This article illustrates the process and obstacles encountered when applying the Common Core's three-part model of determining text complexity to an urban literature text. This analysis revealed how the model privileges language and literacy practices that limit the range of texts used in classrooms through a process of naturalization and by…

Construct Validity in TOEFL iBT Speaking Tasks: Insights from Natural Language Processing

ERIC Educational Resources Information Center

Kyle, Kristopher; Crossley, Scott A.; McNamara, Danielle S.

2016-01-01

This study explores the construct validity of speaking tasks included in the TOEFL iBT (e.g., integrated and independent speaking tasks). Specifically, advanced natural language processing (NLP) tools, MANOVA difference statistics, and discriminant function analyses (DFA) are used to assess the degree to which and in what ways responses to these…

AutoTutor and Family: A Review of 17 Years of Natural Language Tutoring

ERIC Educational Resources Information Center

Nye, Benjamin D.; Graesser, Arthur C.; Hu, Xiangen

2014-01-01

AutoTutor is a natural language tutoring system that has produced learning gains across multiple domains (e.g., computer literacy, physics, critical thinking). In this paper, we review the development, key research findings, and systems that have evolved from AutoTutor. First, the rationale for developing AutoTutor is outlined and the advantages…

What Is a Language?

ERIC Educational Resources Information Center

Le Page, R. B.

A discussion on the nature of language argues the following: (1) the concept of a closed and finite rule system is inadequate for the description of natural languages; (2) as a consequence, the writing of variable rules to modify such rule systems so as to accommodate the properties of natural language is inappropriate; (3) the concept of such…

Language evolution and human-computer interaction

NASA Technical Reports Server (NTRS)

Grudin, Jonathan; Norman, Donald A.

1991-01-01

Many of the issues that confront designers of interactive computer systems also appear in natural language evolution. Natural languages and human-computer interfaces share as their primary mission the support of extended 'dialogues' between responsive entities. Because in each case one participant is a human being, some of the pressures operating on natural languages, causing them to evolve in order to better support such dialogue, also operate on human-computer 'languages' or interfaces. This does not necessarily push interfaces in the direction of natural language - since one entity in this dialogue is not a human, this is not to be expected. Nonetheless, by discerning where the pressures that guide natural language evolution also appear in human-computer interaction, we can contribute to the design of computer systems and obtain a new perspective on natural languages.

Children with Specific Language Impairment and Their Families: A Future View of Nature Plus Nurture and New Technologies for Comprehensive Language Intervention Strategies.

PubMed

Rice, Mabel L

2016-11-01

Future perspectives on children with language impairments are framed from what is known about children with specific language impairment (SLI). A summary of the current state of services is followed by discussion of how these children can be overlooked and misunderstood and consideration of why it is so hard for some children to acquire language when it is effortless for most children. Genetic influences are highlighted, with the suggestion that nature plus nurture should be considered in present as well as future intervention approaches. A nurture perspective highlights the family context of the likelihood of SLI for some of the children. Future models of the causal pathways may provide more specific information to guide gene-treatment decisions, in ways parallel to current personalized medicine approaches. Future treatment options can build on the potential of electronic technologies and social media to provide personalized treatment methods available at a time and place convenient for the person to use as often as desired. The speech-language pathologist could oversee a wide range of treatment options and monitor evidence provided electronically to evaluate progress and plan future treatment steps. Most importantly, future methods can provide lifelong language acquisition activities that maintain the privacy and dignity of persons with language impairment, and in so doing will in turn enhance the effectiveness of speech-language pathologists. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

Natural language acquisition in large scale neural semantic networks

NASA Astrophysics Data System (ADS)

Ealey, Douglas

This thesis puts forward the view that a purely signal- based approach to natural language processing is both plausible and desirable. By questioning the veracity of symbolic representations of meaning, it argues for a unified, non-symbolic model of knowledge representation that is both biologically plausible and, potentially, highly efficient. Processes to generate a grounded, neural form of this model-dubbed the semantic filter-are discussed. The combined effects of local neural organisation, coincident with perceptual maturation, are used to hypothesise its nature. This theoretical model is then validated in light of a number of fundamental neurological constraints and milestones. The mechanisms of semantic and episodic development that the model predicts are then used to explain linguistic properties, such as propositions and verbs, syntax and scripting. To mimic the growth of locally densely connected structures upon an unbounded neural substrate, a system is developed that can grow arbitrarily large, data- dependant structures composed of individual self- organising neural networks. The maturational nature of the data used results in a structure in which the perception of concepts is refined by the networks, but demarcated by subsequent structure. As a consequence, the overall structure shows significant memory and computational benefits, as predicted by the cognitive and neural models. Furthermore, the localised nature of the neural architecture also avoids the increasing error sensitivity and redundancy of traditional systems as the training domain grows. The semantic and episodic filters have been demonstrated to perform as well, or better, than more specialist networks, whilst using significantly larger vocabularies, more complex sentence forms and more natural corpora.

A Comparison of Natural Language Processing Methods for Automated Coding of Motivational Interviewing.

PubMed

Tanana, Michael; Hallgren, Kevin A; Imel, Zac E; Atkins, David C; Srikumar, Vivek

2016-06-01

Motivational interviewing (MI) is an efficacious treatment for substance use disorders and other problem behaviors. Studies on MI fidelity and mechanisms of change typically use human raters to code therapy sessions, which requires considerable time, training, and financial costs. Natural language processing techniques have recently been utilized for coding MI sessions using machine learning techniques, rather than human coders, and preliminary results have suggested these methods hold promise. The current study extends this previous work by introducing two natural language processing models for automatically coding MI sessions via computer. The two models differ in the way they semantically represent session content, utilizing either 1) simple discrete sentence features (DSF model) and 2) more complex recursive neural networks (RNN model). Utterance- and session-level predictions from these models were compared to ratings provided by human coders using a large sample of MI sessions (N=341 sessions; 78,977 clinician and client talk turns) from 6 MI studies. Results show that the DSF model generally had slightly better performance compared to the RNN model. The DSF model had "good" or higher utterance-level agreement with human coders (Cohen's kappa>0.60) for open and closed questions, affirm, giving information, and follow/neutral (all therapist codes); considerably higher agreement was obtained for session-level indices, and many estimates were competitive with human-to-human agreement. However, there was poor agreement for client change talk, client sustain talk, and therapist MI-inconsistent behaviors. Natural language processing methods provide accurate representations of human derived behavioral codes and could offer substantial improvements to the efficiency and scale in which MI mechanisms of change research and fidelity monitoring are conducted. Copyright © 2016 Elsevier Inc. All rights reserved.

Drawing Dynamic Geometry Figures Online with Natural Language for Junior High School Geometry

ERIC Educational Resources Information Center

Wong, Wing-Kwong; Yin, Sheng-Kai; Yang, Chang-Zhe

2012-01-01

This paper presents a tool for drawing dynamic geometric figures by understanding the texts of geometry problems. With the tool, teachers and students can construct dynamic geometric figures on a web page by inputting a geometry problem in natural language. First we need to build the knowledge base for understanding geometry problems. With the…

BT-Nurse: computer generation of natural language shift summaries from complex heterogeneous medical data.

PubMed

Hunter, James; Freer, Yvonne; Gatt, Albert; Reiter, Ehud; Sripada, Somayajulu; Sykes, Cindy; Westwater, Dave

2011-01-01

The BT-Nurse system uses data-to-text technology to automatically generate a natural language nursing shift summary in a neonatal intensive care unit (NICU). The summary is solely based on data held in an electronic patient record system, no additional data-entry is required. BT-Nurse was tested for two months in the Royal Infirmary of Edinburgh NICU. Nurses were asked to rate the understandability, accuracy, and helpfulness of the computer-generated summaries; they were also asked for free-text comments about the summaries. The nurses found the majority of the summaries to be understandable, accurate, and helpful (p<0.001 for all measures). However, nurses also pointed out many deficiencies, especially with regard to extra content they wanted to see in the computer-generated summaries. In conclusion, natural language NICU shift summaries can be automatically generated from an electronic patient record, but our proof-of-concept software needs considerable additional development work before it can be deployed.

Adapting existing natural language processing resources for cardiovascular risk factors identification in clinical notes.

PubMed

Khalifa, Abdulrahman; Meystre, Stéphane

2015-12-01

The 2014 i2b2 natural language processing shared task focused on identifying cardiovascular risk factors such as high blood pressure, high cholesterol levels, obesity and smoking status among other factors found in health records of diabetic patients. In addition, the task involved detecting medications, and time information associated with the extracted data. This paper presents the development and evaluation of a natural language processing (NLP) application conceived for this i2b2 shared task. For increased efficiency, the application main components were adapted from two existing NLP tools implemented in the Apache UIMA framework: Textractor (for dictionary-based lookup) and cTAKES (for preprocessing and smoking status detection). The application achieved a final (micro-averaged) F1-measure of 87.5% on the final evaluation test set. Our attempt was mostly based on existing tools adapted with minimal changes and allowed for satisfying performance with limited development efforts. Copyright © 2015 Elsevier Inc. All rights reserved.

BT-Nurse: computer generation of natural language shift summaries from complex heterogeneous medical data

PubMed Central

Freer, Yvonne; Gatt, Albert; Reiter, Ehud; Sripada, Somayajulu; Sykes, Cindy; Westwater, Dave

2011-01-01

The BT-Nurse system uses data-to-text technology to automatically generate a natural language nursing shift summary in a neonatal intensive care unit (NICU). The summary is solely based on data held in an electronic patient record system, no additional data-entry is required. BT-Nurse was tested for two months in the Royal Infirmary of Edinburgh NICU. Nurses were asked to rate the understandability, accuracy, and helpfulness of the computer-generated summaries; they were also asked for free-text comments about the summaries. The nurses found the majority of the summaries to be understandable, accurate, and helpful (p<0.001 for all measures). However, nurses also pointed out many deficiencies, especially with regard to extra content they wanted to see in the computer-generated summaries. In conclusion, natural language NICU shift summaries can be automatically generated from an electronic patient record, but our proof-of-concept software needs considerable additional development work before it can be deployed. PMID:21724739

Constructing Concept Schemes From Astronomical Telegrams Via Natural Language Clustering

NASA Astrophysics Data System (ADS)

Graham, Matthew; Zhang, M.; Djorgovski, S. G.; Donalek, C.; Drake, A. J.; Mahabal, A.

2012-01-01

The rapidly emerging field of time domain astronomy is one of the most exciting and vibrant new research frontiers, ranging in scientific scope from studies of the Solar System to extreme relativistic astrophysics and cosmology. It is being enabled by a new generation of large synoptic digital sky surveys - LSST, PanStarrs, CRTS - that cover large areas of sky repeatedly, looking for transient objects and phenomena. One of the biggest challenges facing these is the automated classification of transient events, a process that needs machine-processible astronomical knowledge. Semantic technologies enable the formal representation of concepts and relations within a particular domain. ATELs (http://www.astronomerstelegram.org) are a commonly-used means for reporting and commenting upon new astronomical observations of transient sources (supernovae, stellar outbursts, blazar flares, etc). However, they are loose and unstructured and employ scientific natural language for description: this makes automated processing of them - a necessity within the next decade with petascale data rates - a challenge. Nevertheless they represent a potentially rich corpus of information that could lead to new and valuable insights into transient phenomena. This project lies in the cutting-edge field of astrosemantics, a branch of astroinformatics, which applies semantic technologies to astronomy. The ATELs have been used to develop an appropriate concept scheme - a representation of the information they contain - for transient astronomy using hierarchical clustering of processed natural language. This allows us to automatically organize ATELs based on the vocabulary used. We conclude that we can use simple algorithms to process and extract meaning from astronomical textual data.

Natural Language Based Multimodal Interface for UAV Mission Planning

NASA Technical Reports Server (NTRS)

Chandarana, Meghan; Meszaros, Erica L.; Trujillo, Anna; Allen, B. Danette

2017-01-01

As the number of viable applications for unmanned aerial vehicle (UAV) systems increases at an exponential rate, interfaces that reduce the reliance on highly skilled engineers and pilots must be developed. Recent work aims to make use of common human communication modalities such as speech and gesture. This paper explores a multimodal natural language interface that uses a combination of speech and gesture input modalities to build complex UAV flight paths by defining trajectory segment primitives. Gesture inputs are used to define the general shape of a segment while speech inputs provide additional geometric information needed to fully characterize a trajectory segment. A user study is conducted in order to evaluate the efficacy of the multimodal interface.

Social Network Development, Language Use, and Language Acquisition during Study Abroad: Arabic Language Learners' Perspectives

ERIC Educational Resources Information Center

Dewey, Dan P.; Belnap, R. Kirk; Hillstrom, Rebecca

2013-01-01

Language learners and educators have subscribed to the belief that those who go abroad will have many opportunities to use the target language and will naturally become proficient. They also assume that language learners will develop relationships with native speakers allowing them to use the language and become more fluent, an assumption…

Strategies for searching medical natural language text. Distribution of words in the anatomic diagnoses of 7000 autopsy subjects.

PubMed Central

Moore, G. W.; Hutchins, G. M.; Miller, R. E.

1984-01-01

Computerized indexing and retrieval of medical records is increasingly important; but the use of natural language versus coded languages (SNOP, SNOMED) for this purpose remains controversial. In an effort to develop search strategies for natural language text, the authors examined the anatomic diagnosis reports by computer for 7000 consecutive autopsy subjects spanning a 13-year period at The Johns Hopkins Hospital. There were 923,657 words, 11,642 of them distinct. The authors observed an average of 1052 keystrokes, 28 lines, and 131 words per autopsy report, with an average 4.6 words per line and 7.0 letters per word. The entire text file represented 921 hours of secretarial effort. Words ranged in frequency from 33,959 occurrences of "and" to one occurrence for each of 3398 different words. Searches for rare diseases with unique names or for representative examples of common diseases were most readily performed with the use of computer-printed key word in context (KWIC) books. For uncommon diseases designated by commonly used terms (such as "cystic fibrosis"), needs were best served by a computerized search for logical combinations of key words. In an unbalanced word distribution, each conjunction (logical and) search should be performed in ascending order of word frequency; but each alternation (logical inclusive or) search should be performed in descending order of word frequency. Natural language text searches will assume a larger role in medical records analysis as the labor-intensive procedure of translation into a coded language becomes more costly, compared with the computer-intensive procedure of text searching. PMID:6546837

Dynamical Languages

NASA Astrophysics Data System (ADS)

Xie, Huimin

The following sections are included: * Definition of Dynamical Languages * Distinct Excluded Blocks * Definition and Properties * L and L″ in Chomsky Hierarchy * A Natural Equivalence Relation * Symbolic Flows * Symbolic Flows and Dynamical Languages * Subshifts of Finite Type * Sofic Systems * Graphs and Dynamical Languages * Graphs and Shannon-Graphs * Transitive Languages * Topological Entropy

Visual sign phonology: insights into human reading and language from a natural soundless phonology.

PubMed

Petitto, L A; Langdon, C; Stone, A; Andriola, D; Kartheiser, G; Cochran, C

2016-11-01

Among the most prevailing assumptions in science and society about the human reading process is that sound and sound-based phonology are critical to young readers. The child's sound-to-letter decoding is viewed as universal and vital to deriving meaning from print. We offer a different view. The crucial link for early reading success is not between segmental sounds and print. Instead the human brain's capacity to segment, categorize, and discern linguistic patterning makes possible the capacity to segment all languages. This biological process includes the segmentation of languages on the hands in signed languages. Exposure to natural sign language in early life equally affords the child's discovery of silent segmental units in visual sign phonology (VSP) that can also facilitate segmental decoding of print. We consider powerful biological evidence about the brain, how it builds sound and sign phonology, and why sound and sign phonology are equally important in language learning and reading. We offer a testable theoretical account, reading model, and predictions about how VSP can facilitate segmentation and mapping between print and meaning. We explain how VSP can be a powerful facilitator of all children's reading success (deaf and hearing)-an account with profound transformative impact on learning to read in deaf children with different language backgrounds. The existence of VSP has important implications for understanding core properties of all human language and reading, challenges assumptions about language and reading as being tied to sound, and provides novel insight into a remarkable biological equivalence in signed and spoken languages. WIREs Cogn Sci 2016, 7:366-381. doi: 10.1002/wcs.1404 For further resources related to this article, please visit the WIREs website. © 2016 Wiley Periodicals, Inc.

Training Parents to Use the Natural Language Paradigm to Increase Their Autistic Children's Speech.

ERIC Educational Resources Information Center

Laski, Karen E.; And Others

1988-01-01

Parents of four nonverbal and four echolalic autistic children, aged five-nine, were trained to increase their children's speech by using the Natural Language Paradigm. Following training, parents increased the frequency with which they required their children to speak, and children increased the frequency of their verbalizations in three…

Coupling ontology driven semantic representation with multilingual natural language generation for tuning international terminologies.

PubMed

Rassinoux, Anne-Marie; Baud, Robert H; Rodrigues, Jean-Marie; Lovis, Christian; Geissbühler, Antoine

2007-01-01

The importance of clinical communication between providers, consumers and others, as well as the requisite for computer interoperability, strengthens the need for sharing common accepted terminologies. Under the directives of the World Health Organization (WHO), an approach is currently being conducted in Australia to adopt a standardized terminology for medical procedures that is intended to become an international reference. In order to achieve such a standard, a collaborative approach is adopted, in line with the successful experiment conducted for the development of the new French coding system CCAM. Different coding centres are involved in setting up a semantic representation of each term using a formal ontological structure expressed through a logic-based representation language. From this language-independent representation, multilingual natural language generation (NLG) is performed to produce noun phrases in various languages that are further compared for consistency with the original terms. Outcomes are presented for the assessment of the International Classification of Health Interventions (ICHI) and its translation into Portuguese. The initial results clearly emphasize the feasibility and cost-effectiveness of the proposed method for handling both a different classification and an additional language. NLG tools, based on ontology driven semantic representation, facilitate the discovery of ambiguous and inconsistent terms, and, as such, should be promoted for establishing coherent international terminologies.

Abductive Equivalential Translation and its application to Natural Language Database Interfacing

NASA Astrophysics Data System (ADS)

Rayner, Manny

1994-05-01

The thesis describes a logical formalization of natural-language database interfacing. We assume the existence of a ``natural language engine'' capable of mediating between surface linguistic string and their representations as ``literal'' logical forms: the focus of interest will be the question of relating ``literal'' logical forms to representations in terms of primitives meaningful to the underlying database engine. We begin by describing the nature of the problem, and show how a variety of interface functionalities can be considered as instances of a type of formal inference task which we call ``Abductive Equivalential Translation'' (AET); functionalities which can be reduced to this form include answering questions, responding to commands, reasoning about the completeness of answers, answering meta-questions of type ``Do you know...'', and generating assertions and questions. In each case, a ``linguistic domain theory'' (LDT) Γ and an input formula F are given, and the goal is to construct a formula with certain properties which is equivalent to F, given Γ and a set of permitted assumptions. If the LDT is of a certain specified type, whose formulas are either conditional equivalences or Horn-clauses, we show that the AET problem can be reduced to a goal-directed inference method. We present an abstract description of this method, and sketch its realization in Prolog. The relationship between AET and several problems previously discussed in the literature is discussed. In particular, we show how AET can provide a simple and elegant solution to the so-called ``Doctor on Board'' problem, and in effect allows a ``relativization'' of the Closed World Assumption. The ideas in the thesis have all been implemented concretely within the SRI CLARE project, using a real projects and payments database. The LDT for the example database is described in detail, and examples of the types of functionality that can be achieved within the example domain are presented.

Unlocking echocardiogram measurements for heart disease research through natural language processing.

PubMed

Patterson, Olga V; Freiberg, Matthew S; Skanderson, Melissa; J Fodeh, Samah; Brandt, Cynthia A; DuVall, Scott L

2017-06-12

In order to investigate the mechanisms of cardiovascular disease in HIV infected and uninfected patients, an analysis of echocardiogram reports is required for a large longitudinal multi-center study. A natural language processing system using a dictionary lookup, rules, and patterns was developed to extract heart function measurements that are typically recorded in echocardiogram reports as measurement-value pairs. Curated semantic bootstrapping was used to create a custom dictionary that extends existing terminologies based on terms that actually appear in the medical record. A novel disambiguation method based on semantic constraints was created to identify and discard erroneous alternative definitions of the measurement terms. The system was built utilizing a scalable framework, making it available for processing large datasets. The system was developed for and validated on notes from three sources: general clinic notes, echocardiogram reports, and radiology reports. The system achieved F-scores of 0.872, 0.844, and 0.877 with precision of 0.936, 0.982, and 0.969 for each dataset respectively averaged across all extracted values. Left ventricular ejection fraction (LVEF) is the most frequently extracted measurement. The precision of extraction of the LVEF measure ranged from 0.968 to 1.0 across different document types. This system illustrates the feasibility and effectiveness of a large-scale information extraction on clinical data. New clinical questions can be addressed in the domain of heart failure using retrospective clinical data analysis because key heart function measurements can be successfully extracted using natural language processing.

Self-Regulated Learning in Learning Environments with Pedagogical Agents that Interact in Natural Language

ERIC Educational Resources Information Center

Graesser, Arthur; McNamara, Danielle

2010-01-01

This article discusses the occurrence and measurement of self-regulated learning (SRL) both in human tutoring and in computer tutors with agents that hold conversations with students in natural language and help them learn at deeper levels. One challenge in building these computer tutors is to accommodate, encourage, and scaffold SRL because these…

Formal ontology for natural language processing and the integration of biomedical databases.

PubMed

Simon, Jonathan; Dos Santos, Mariana; Fielding, James; Smith, Barry

2006-01-01

The central hypothesis underlying this communication is that the methodology and conceptual rigor of a philosophically inspired formal ontology can bring significant benefits in the development and maintenance of application ontologies [A. Flett, M. Dos Santos, W. Ceusters, Some Ontology Engineering Procedures and their Supporting Technologies, EKAW2002, 2003]. This hypothesis has been tested in the collaboration between Language and Computing (L&C), a company specializing in software for supporting natural language processing especially in the medical field, and the Institute for Formal Ontology and Medical Information Science (IFOMIS), an academic research institution concerned with the theoretical foundations of ontology. In the course of this collaboration L&C's ontology, LinKBase, which is designed to integrate and support reasoning across a plurality of external databases, has been subjected to a thorough auditing on the basis of the principles underlying IFOMIS's Basic Formal Ontology (BFO) [B. Smith, Basic Formal Ontology, 2002. http://ontology.buffalo.edu/bfo]. The goal is to transform a large terminology-based ontology into one with the ability to support reasoning applications. Our general procedure has been the implementation of a meta-ontological definition space in which the definitions of all the concepts and relations in LinKBase are standardized in the framework of first-order logic. In this paper we describe how this principles-based standardization has led to a greater degree of internal coherence of the LinKBase structure, and how it has facilitated the construction of mappings between external databases using LinKBase as translation hub. We argue that the collaboration here described represents a new phase in the quest to solve the so-called "Tower of Babel" problem of ontology integration [F. Montayne, J. Flanagan, Formal Ontology: The Foundation for Natural Language Processing, 2003. http://www.landcglobal.com/].

A Requirements-Based Exploration of Open-Source Software Development Projects--Towards a Natural Language Processing Software Analysis Framework

ERIC Educational Resources Information Center

Vlas, Radu Eduard

2012-01-01

Open source projects do have requirements; they are, however, mostly informal, text descriptions found in requests, forums, and other correspondence. Understanding such requirements provides insight into the nature of open source projects. Unfortunately, manual analysis of natural language requirements is time-consuming, and for large projects,…

Incremental Bayesian Category Learning From Natural Language.

PubMed

Frermann, Lea; Lapata, Mirella

2016-08-01

Models of category learning have been extensively studied in cognitive science and primarily tested on perceptual abstractions or artificial stimuli. In this paper, we focus on categories acquired from natural language stimuli, that is, words (e.g., chair is a member of the furniture category). We present a Bayesian model that, unlike previous work, learns both categories and their features in a single process. We model category induction as two interrelated subproblems: (a) the acquisition of features that discriminate among categories, and (b) the grouping of concepts into categories based on those features. Our model learns categories incrementally using particle filters, a sequential Monte Carlo method commonly used for approximate probabilistic inference that sequentially integrates newly observed data and can be viewed as a plausible mechanism for human learning. Experimental results show that our incremental learner obtains meaningful categories which yield a closer fit to behavioral data compared to related models while at the same time acquiring features which characterize the learned categories. (An earlier version of this work was published in Frermann and Lapata .). Copyright © 2015 Cognitive Science Society, Inc.

Ulisse Aldrovandi's Color Sensibility: Natural History, Language and the Lay Color Practices of Renaissance Virtuosi.

PubMed

Pugliano, Valentina

2015-01-01

Famed for his collection of drawings of naturalia and his thoughts on the relationship between painting and natural knowledge, it now appears that the Bolognese naturalist Ulisse Aldrovandi (1522-1605) also pondered specifically color and pigments, compiling not only lists and diagrams of color terms but also a full-length unpublished manuscript entitled De coloribus or Trattato dei colori. Introducing these writings for the first time, this article portrays a scholar not so much interested in the materiality of pigment production, as in the cultural history of hues. It argues that these writings constituted an effort to build a language of color, in the sense both of a standard nomenclature of hues and of a lexicon, a dictionary of their denotations and connotations as documented in the literature of ancients and moderns. This language would serve the naturalist in his artistic patronage and his natural historical studies, where color was considered one of the most reliable signs for the correct identification of specimens, and a guarantee of accuracy in their illustration. Far from being an exception, Aldrovandi's 'color sensibility'spoke of that of his university-educated nature-loving peers.

Programming Languages.

ERIC Educational Resources Information Center

Tesler, Lawrence G.

1984-01-01

Discusses the nature of programing languages, considering the features of BASIC, LOGO, PASCAL, COBOL, FORTH, APL, and LISP. Also discusses machine/assembly codes, the operation of a compiler, and trends in the evolution of programing languages (including interest in notational systems called object-oriented languages). (JN)

A natural language screening measure for motivation to change.

PubMed

Miller, William R; Johnson, Wendy R

2008-09-01

Client motivation for change, a topic of high interest to addiction clinicians, is multidimensional and complex, and many different approaches to measurement have been tried. The current effort drew on psycholinguistic research on natural language that is used by clients to describe their own motivation. Seven addiction treatment sites participated in the development of a simple scale to measure client motivation. Twelve items were drafted to represent six potential dimensions of motivation for change that occur in natural discourse. The maximum self-rating of motivation (10 on a 0-10 scale) was the median score on all items, and 43% of respondents rated 10 on all 12 items - a substantial ceiling effect. From 1035 responses, three factors emerged representing importance, ability, and commitment - constructs that are also reflected in several theoretical models of motivation. A 3-item version of the scale, with one marker item for each of these constructs, accounted for 81% of variance in the full scale. The three items are: 1. It is important for me to . . . 2. I could . . . and 3. I am trying to . . . This offers a quick (1-minute) assessment of clients' self-reported motivation for change.

Automatic Parsing of Parental Verbal Input

PubMed Central

Sagae, Kenji; MacWhinney, Brian; Lavie, Alon

2006-01-01

To evaluate theoretical proposals regarding the course of child language acquisition, researchers often need to rely on the processing of large numbers of syntactically parsed utterances, both from children and their parents. Because it is so difficult to do this by hand, there are currently no parsed corpora of child language input data. To automate this process, we developed a system that combined the MOR tagger, a rule-based parser, and statistical disambiguation techniques. The resultant system obtained nearly 80% correct parses for the sentences spoken to children. To achieve this level, we had to construct a particular processing sequence that minimizes problems caused by the coverage/ambiguity trade-off in parser design. These procedures are particularly appropriate for use with the CHILDES database, an international corpus of transcripts. The data and programs are now freely available over the Internet. PMID:15190707

Learning for Semantic Parsing and Natural Language Generation Using Statistical Machine Translation Techniques

DTIC Science & Technology

2007-08-01

In this domain, queries typically show a deeply nested structure, which makes the semantic parsing task rather challenging , e.g.: What states border...only 80% of the GEOQUERY queries are semantically tractable, which shows that GEOQUERY is indeed a more challenging domain than ATIS. Note that none...a particularly challenging task, because of the inherent ambiguity of natural languages on both sides. It has inspired a large body of research. In

Using a Language Generation System for Second Language Learning.

ERIC Educational Resources Information Center

Levison, Michael; Lessard, Greg

1996-01-01

Describes a language generation system, which, given data files describing a natural language, generates utterances of the class the user has specified. The system can exercise control over the syntax, lexicon, morphology, and semantics of the language. This article explores a range of the system's potential applications to second-language…

Using the Natural Language Paradigm (NLP) to increase vocalizations of older adults with cognitive impairments.

PubMed

Leblanc, Linda A; Geiger, Kaneen B; Sautter, Rachael A; Sidener, Tina M

2007-01-01

The Natural Language Paradigm (NLP) has proven effective in increasing spontaneous verbalizations for children with autism. This study investigated the use of NLP with older adults with cognitive impairments served at a leisure-based adult day program for seniors. Three individuals with limited spontaneous use of functional language participated in a multiple baseline design across participants. Data were collected on appropriate and inappropriate vocalizations with appropriate vocalizations coded as prompted or unprompted during baseline and treatment sessions. All participants experienced increases in appropriate speech during NLP with variable response patterns. Additionally, the two participants with substantial inappropriate vocalizations showed decreases in inappropriate speech. Implications for intervention in day programs are discussed.

BIBLIOGRAPHY ON LANGUAGE DEVELOPMENT.

ERIC Educational Resources Information Center

Harvard Univ., Cambridge, MA. Graduate School of Education.

THIS BIBLIOGRAPHY LISTS MATERIAL ON VARIOUS ASPECTS OF LANGUAGE DEVELOPMENT. APPROXIMATELY 65 UNANNOTATED REFERENCES ARE PROVIDED TO DOCUMENTS DATING FROM 1958 TO 1966. JOURNALS, BOOKS, AND REPORT MATERIALS ARE LISTED. SUBJECT AREAS INCLUDED ARE THE NATURE OF LANGUAGE, LINGUISTICS, LANGUAGE LEARNING, LANGUAGE SKILLS, LANGUAGE PATTERNS, AND…

The language faculty that wasn't: a usage-based account of natural language recursion

PubMed Central

Christiansen, Morten H.; Chater, Nick

2015-01-01

In the generative tradition, the language faculty has been shrinking—perhaps to include only the mechanism of recursion. This paper argues that even this view of the language faculty is too expansive. We first argue that a language faculty is difficult to reconcile with evolutionary considerations. We then focus on recursion as a detailed case study, arguing that our ability to process recursive structure does not rely on recursion as a property of the grammar, but instead emerges gradually by piggybacking on domain-general sequence learning abilities. Evidence from genetics, comparative work on non-human primates, and cognitive neuroscience suggests that humans have evolved complex sequence learning skills, which were subsequently pressed into service to accommodate language. Constraints on sequence learning therefore have played an important role in shaping the cultural evolution of linguistic structure, including our limited abilities for processing recursive structure. Finally, we re-evaluate some of the key considerations that have often been taken to require the postulation of a language faculty. PMID:26379567

The language faculty that wasn't: a usage-based account of natural language recursion.

PubMed

Christiansen, Morten H; Chater, Nick

2015-01-01

In the generative tradition, the language faculty has been shrinking-perhaps to include only the mechanism of recursion. This paper argues that even this view of the language faculty is too expansive. We first argue that a language faculty is difficult to reconcile with evolutionary considerations. We then focus on recursion as a detailed case study, arguing that our ability to process recursive structure does not rely on recursion as a property of the grammar, but instead emerges gradually by piggybacking on domain-general sequence learning abilities. Evidence from genetics, comparative work on non-human primates, and cognitive neuroscience suggests that humans have evolved complex sequence learning skills, which were subsequently pressed into service to accommodate language. Constraints on sequence learning therefore have played an important role in shaping the cultural evolution of linguistic structure, including our limited abilities for processing recursive structure. Finally, we re-evaluate some of the key considerations that have often been taken to require the postulation of a language faculty.

Natural Language Description of Emotion

ERIC Educational Resources Information Center

Kazemzadeh, Abe

2013-01-01

This dissertation studies how people describe emotions with language and how computers can simulate this descriptive behavior. Although many non-human animals can express their current emotions as social signals, only humans can communicate about emotions symbolically. This symbolic communication of emotion allows us to talk about emotions that we…

nala: text mining natural language mutation mentions

PubMed Central

Cejuela, Juan Miguel; Bojchevski, Aleksandar; Uhlig, Carsten; Bekmukhametov, Rustem; Kumar Karn, Sanjeev; Mahmuti, Shpend; Baghudana, Ashish; Dubey, Ankit; Satagopam, Venkata P.; Rost, Burkhard

2017-01-01

Abstract Motivation: The extraction of sequence variants from the literature remains an important task. Existing methods primarily target standard (ST) mutation mentions (e.g. ‘E6V’), leaving relevant mentions natural language (NL) largely untapped (e.g. ‘glutamic acid was substituted by valine at residue 6’). Results: We introduced three new corpora suggesting named-entity recognition (NER) to be more challenging than anticipated: 28–77% of all articles contained mentions only available in NL. Our new method nala captured NL and ST by combining conditional random fields with word embedding features learned unsupervised from the entire PubMed. In our hands, nala substantially outperformed the state-of-the-art. For instance, we compared all unique mentions in new discoveries correctly detected by any of three methods (SETH, tmVar, or nala). Neither SETH nor tmVar discovered anything missed by nala, while nala uniquely tagged 33% mentions. For NL mentions the corresponding value shot up to 100% nala-only. Availability and Implementation: Source code, API and corpora freely available at: http://tagtog.net/-corpora/IDP4+. Contact: nala@rostlab.org Supplementary information: Supplementary data are available at Bioinformatics online. PMID:28200120

"Speaking English Naturally": The Language Ideologies of English as an Official Language at a Korean University

ERIC Educational Resources Information Center

Choi, Jinsook

2016-01-01

This study explores language ideologies of English at a Korean university where English has been adopted as an official language. This study draws on ethnographic data in order to understand how speakers respond to and experience the institutional language policy. The findings show that language ideologies in this university represent the…

How Much Language Is Enough? Some Immigrant Language Lessons from Canada and Germany. Discussion Paper.

ERIC Educational Resources Information Center

DeVoretz, Don J.; Hinte, Holger; Werner, Christiane

Germany and Canada are at opposite ends of the debate over language integration and ascension to citizenship. German naturalization contains an explicit language criterion for naturalization. The first German immigration act will not only concentrate on control aspects but also focus on language as a criterion for legal immigration. Canada does…

Automatic generation of natural language nursing shift summaries in neonatal intensive care: BT-Nurse.

PubMed

Hunter, James; Freer, Yvonne; Gatt, Albert; Reiter, Ehud; Sripada, Somayajulu; Sykes, Cindy

2012-11-01

Our objective was to determine whether and how a computer system could automatically generate helpful natural language nursing shift summaries solely from an electronic patient record system, in a neonatal intensive care unit (NICU). A system was developed which automatically generates partial NICU shift summaries (for the respiratory and cardiovascular systems), using data-to-text technology. It was evaluated for 2 months in the NICU at the Royal Infirmary of Edinburgh, under supervision. In an on-ward evaluation, a substantial majority of the summaries was found by outgoing and incoming nurses to be understandable (90%), and a majority was found to be accurate (70%), and helpful (59%). The evaluation also served to identify some outstanding issues, especially with regard to extra content the nurses wanted to see in the computer-generated summaries. It is technically possible automatically to generate limited natural language NICU shift summaries from an electronic patient record. However, it proved difficult to handle electronic data that was intended primarily for display to the medical staff, and considerable engineering effort would be required to create a deployable system from our proof-of-concept software. Copyright © 2012 Elsevier B.V. All rights reserved.

Computational Nonlinear Morphology with Emphasis on Semitic Languages. Studies in Natural Language Processing.

ERIC Educational Resources Information Center

Kiraz, George Anton

This book presents a tractable computational model that can cope with complex morphological operations, especially in Semitic languages, and less complex morphological systems present in Western languages. It outlines a new generalized regular rewrite rule system that uses multiple finite-state automata to cater to root-and-pattern morphology,…

Optimizing annotation resources for natural language de-identification via a game theoretic framework.

PubMed

Li, Muqun; Carrell, David; Aberdeen, John; Hirschman, Lynette; Kirby, Jacqueline; Li, Bo; Vorobeychik, Yevgeniy; Malin, Bradley A

2016-06-01

Electronic medical records (EMRs) are increasingly repurposed for activities beyond clinical care, such as to support translational research and public policy analysis. To mitigate privacy risks, healthcare organizations (HCOs) aim to remove potentially identifying patient information. A substantial quantity of EMR data is in natural language form and there are concerns that automated tools for detecting identifiers are imperfect and leak information that can be exploited by ill-intentioned data recipients. Thus, HCOs have been encouraged to invest as much effort as possible to find and detect potential identifiers, but such a strategy assumes the recipients are sufficiently incentivized and capable of exploiting leaked identifiers. In practice, such an assumption may not hold true and HCOs may overinvest in de-identification technology. The goal of this study is to design a natural language de-identification framework, rooted in game theory, which enables an HCO to optimize their investments given the expected capabilities of an adversarial recipient. We introduce a Stackelberg game to balance risk and utility in natural language de-identification. This game represents a cost-benefit model that enables an HCO with a fixed budget to minimize their investment in the de-identification process. We evaluate this model by assessing the overall payoff to the HCO and the adversary using 2100 clinical notes from Vanderbilt University Medical Center. We simulate several policy alternatives using a range of parameters, including the cost of training a de-identification model and the loss in data utility due to the removal of terms that are not identifiers. In addition, we compare policy options where, when an attacker is fined for misuse, a monetary penalty is paid to the publishing HCO as opposed to a third party (e.g., a federal regulator). Our results show that when an HCO is forced to exhaust a limited budget (set to $2000 in the study), the precision and recall of the

DDM at Work. Reply to comments on "Dependency distance: A new perspective on syntactic patterns in natural languages"

NASA Astrophysics Data System (ADS)

Xu, Chunshan; Liang, Junying; Liu, Haitao

2017-07-01

We provide responses to the commentaries in this volume to evaluate, clarify and extend some of the arguments in Dependency distance: A new perspective on syntactic patterns in natural languages. Evidences show that DDM (dependency distance minimization) is an important linguistic universal, biologically or cognitively motivated, in shaping the language system. As a general tendency, DDM works quite well in theoretical argumentations as well as practical applications. However, this does not mean that DDM is the only linguistic universal that works: it is highly possible that other factors, which might be biologically, physically, socially or culturally motivated, work as well to jointly mold languages.

Linguistics in Language Education

ERIC Educational Resources Information Center

Kumar, Rajesh; Yunus, Reva

2014-01-01

This article looks at the contribution of insights from theoretical linguistics to an understanding of language acquisition and the nature of language in terms of their potential benefit to language education. We examine the ideas of innateness and universal language faculty, as well as multilingualism and the language-society relationship. Modern…

The Oscillopathic Nature of Language Deficits in Autism: From Genes to Language Evolution

PubMed Central

Benítez-Burraco, Antonio; Murphy, Elliot

2016-01-01

Autism spectrum disorders (ASD) are pervasive neurodevelopmental disorders involving a number of deficits to linguistic cognition. The gap between genetics and the pathophysiology of ASD remains open, in particular regarding its distinctive linguistic profile. The goal of this article is to attempt to bridge this gap, focusing on how the autistic brain processes language, particularly through the perspective of brain rhythms. Due to the phenomenon of pleiotropy, which may take some decades to overcome, we believe that studies of brain rhythms, which are not faced with problems of this scale, may constitute a more tractable route to interpreting language deficits in ASD and eventually other neurocognitive disorders. Building on recent attempts to link neural oscillations to certain computational primitives of language, we show that interpreting language deficits in ASD as oscillopathic traits is a potentially fruitful way to construct successful endophenotypes of this condition. Additionally, we will show that candidate genes for ASD are overrepresented among the genes that played a role in the evolution of language. These genes include (and are related to) genes involved in brain rhythmicity. We hope that the type of steps taken here will additionally lead to a better understanding of the comorbidity, heterogeneity, and variability of ASD, and may help achieve a better treatment of the affected populations. PMID:27047363

Behind the scenes: A medical natural language processing project.

PubMed

Wu, Joy T; Dernoncourt, Franck; Gehrmann, Sebastian; Tyler, Patrick D; Moseley, Edward T; Carlson, Eric T; Grant, David W; Li, Yeran; Welt, Jonathan; Celi, Leo Anthony

2018-04-01

Advancement of Artificial Intelligence (AI) capabilities in medicine can help address many pressing problems in healthcare. However, AI research endeavors in healthcare may not be clinically relevant, may have unrealistic expectations, or may not be explicit enough about their limitations. A diverse and well-functioning multidisciplinary team (MDT) can help identify appropriate and achievable AI research agendas in healthcare, and advance medical AI technologies by developing AI algorithms as well as addressing the shortage of appropriately labeled datasets for machine learning. In this paper, our team of engineers, clinicians and machine learning experts share their experience and lessons learned from their two-year-long collaboration on a natural language processing (NLP) research project. We highlight specific challenges encountered in cross-disciplinary teamwork, dataset creation for NLP research, and expectation setting for current medical AI technologies. Copyright © 2017. Published by Elsevier B.V.

Two models of minimalist, incremental syntactic analysis.

PubMed

Stabler, Edward P

2013-07-01

Minimalist grammars (MGs) and multiple context-free grammars (MCFGs) are weakly equivalent in the sense that they define the same languages, a large mildly context-sensitive class that properly includes context-free languages. But in addition, for each MG, there is an MCFG which is strongly equivalent in the sense that it defines the same language with isomorphic derivations. However, the structure-building rules of MGs but not MCFGs are defined in a way that generalizes across categories. Consequently, MGs can be exponentially more succinct than their MCFG equivalents, and this difference shows in parsing models too. An incremental, top-down beam parser for MGs is defined here, sound and complete for all MGs, and hence also capable of parsing all MCFG languages. But since the parser represents its grammar transparently, the relative succinctness of MGs is again evident. Although the determinants of MG structure are narrowly and discretely defined, probabilistic influences from a much broader domain can influence even the earliest analytic steps, allowing frequency and context effects to come early and from almost anywhere, as expected in incremental models. Copyright © 2013 Cognitive Science Society, Inc.

Sociolinguistic Typology and Sign Languages

PubMed Central

Schembri, Adam; Fenlon, Jordan; Cormier, Kearsy; Johnston, Trevor

2018-01-01

This paper examines the possible relationship between proposed social determinants of morphological ‘complexity’ and how this contributes to linguistic diversity, specifically via the typological nature of the sign languages of deaf communities. We sketch how the notion of morphological complexity, as defined by Trudgill (2011), applies to sign languages. Using these criteria, sign languages appear to be languages with low to moderate levels of morphological complexity. This may partly reflect the influence of key social characteristics of communities on the typological nature of languages. Although many deaf communities are relatively small and may involve dense social networks (both social characteristics that Trudgill claimed may lend themselves to morphological ‘complexification’), the picture is complicated by the highly variable nature of the sign language acquisition for most deaf people, and the ongoing contact between native signers, hearing non-native signers, and those deaf individuals who only acquire sign languages in later childhood and early adulthood. These are all factors that may work against the emergence of morphological complexification. The relationship between linguistic typology and these key social factors may lead to a better understanding of the nature of sign language grammar. This perspective stands in contrast to other work where sign languages are sometimes presented as having complex morphology despite being young languages (e.g., Aronoff et al., 2005); in some descriptions, the social determinants of morphological complexity have not received much attention, nor has the notion of complexity itself been specifically explored. PMID:29515506

Sociolinguistic Typology and Sign Languages.

PubMed

Schembri, Adam; Fenlon, Jordan; Cormier, Kearsy; Johnston, Trevor

2018-01-01

This paper examines the possible relationship between proposed social determinants of morphological 'complexity' and how this contributes to linguistic diversity, specifically via the typological nature of the sign languages of deaf communities. We sketch how the notion of morphological complexity, as defined by Trudgill (2011), applies to sign languages. Using these criteria, sign languages appear to be languages with low to moderate levels of morphological complexity. This may partly reflect the influence of key social characteristics of communities on the typological nature of languages. Although many deaf communities are relatively small and may involve dense social networks (both social characteristics that Trudgill claimed may lend themselves to morphological 'complexification'), the picture is complicated by the highly variable nature of the sign language acquisition for most deaf people, and the ongoing contact between native signers, hearing non-native signers, and those deaf individuals who only acquire sign languages in later childhood and early adulthood. These are all factors that may work against the emergence of morphological complexification. The relationship between linguistic typology and these key social factors may lead to a better understanding of the nature of sign language grammar. This perspective stands in contrast to other work where sign languages are sometimes presented as having complex morphology despite being young languages (e.g., Aronoff et al., 2005); in some descriptions, the social determinants of morphological complexity have not received much attention, nor has the notion of complexity itself been specifically explored.

Language-Related Learning Disabilities: Their Nature and Treatment.

ERIC Educational Resources Information Center

Gerber, Adele

This book is intended for graduate students and practitioners serving the needs of individuals with language-related learning disabilities in regular education, special education, and speech-language pathology. Some chapters are contributed by other authors. An introductory chapter chronicles historical trends in understanding and addressing…

LABORATORY PROCESS CONTROLLER USING NATURAL LANGUAGE COMMANDS FROM A PERSONAL COMPUTER

NASA Technical Reports Server (NTRS)

Will, H.

1994-01-01

The complex environment of the typical research laboratory requires flexible process control. This program provides natural language process control from an IBM PC or compatible machine. Sometimes process control schedules require changes frequently, even several times per day. These changes may include adding, deleting, and rearranging steps in a process. This program sets up a process control system that can either run without an operator, or be run by workers with limited programming skills. The software system includes three programs. Two of the programs, written in FORTRAN77, record data and control research processes. The third program, written in Pascal, generates the FORTRAN subroutines used by the other two programs to identify the user commands with the user-written device drivers. The software system also includes an input data set which allows the user to define the user commands which are to be executed by the computer. To set the system up the operator writes device driver routines for all of the controlled devices. Once set up, this system requires only an input file containing natural language command lines which tell the system what to do and when to do it. The operator can make up custom commands for operating and taking data from external research equipment at any time of the day or night without the operator in attendance. This process control system requires a personal computer operating under MS-DOS with suitable hardware interfaces to all controlled devices. The program requires a FORTRAN77 compiler and user-written device drivers. This program was developed in 1989 and has a memory requirement of about 62 Kbytes.

Building gold standard corpora for medical natural language processing tasks.

PubMed

Deleger, Louise; Li, Qi; Lingren, Todd; Kaiser, Megan; Molnar, Katalin; Stoutenborough, Laura; Kouril, Michal; Marsolo, Keith; Solti, Imre

2012-01-01

We present the construction of three annotated corpora to serve as gold standards for medical natural language processing (NLP) tasks. Clinical notes from the medical record, clinical trial announcements, and FDA drug labels are annotated. We report high inter-annotator agreements (overall F-measures between 0.8467 and 0.9176) for the annotation of Personal Health Information (PHI) elements for a de-identification task and of medications, diseases/disorders, and signs/symptoms for information extraction (IE) task. The annotated corpora of clinical trials and FDA labels will be publicly released and to facilitate translational NLP tasks that require cross-corpora interoperability (e.g. clinical trial eligibility screening) their annotation schemas are aligned with a large scale, NIH-funded clinical text annotation project.

Creation of structured documentation templates using Natural Language Processing techniques.

PubMed

Kashyap, Vipul; Turchin, Alexander; Morin, Laura; Chang, Frank; Li, Qi; Hongsermeier, Tonya

2006-01-01

Structured Clinical Documentation is a fundamental component of the healthcare enterprise, linking both clinical (e.g., electronic health record, clinical decision support) and administrative functions (e.g., evaluation and management coding, billing). One of the challenges in creating good quality documentation templates has been the inability to address specialized clinical disciplines and adapt to local clinical practices. A one-size-fits-all approach leads to poor adoption and inefficiencies in the documentation process. On the other hand, the cost associated with manual generation of documentation templates is significant. Consequently there is a need for at least partial automation of the template generation process. We propose an approach and methodology for the creation of structured documentation templates for diabetes using Natural Language Processing (NLP).

The Relationship between Mathematics and Language: Academic Implications for Children with Specific Language Impairment and English Language Learners

ERIC Educational Resources Information Center

Alt, Mary; Arizmendi, Genesis D.; Beal, Carole R.

2014-01-01

Purpose: The present study examined the relationship between mathematics and language to better understand the nature of the deficit and the academic implications associated with specific language impairment (SLI) and academic implications for English language learners (ELLs). Method: School-age children (N = 61; 20 SLI, 20 ELL, 21 native…

A Risk Assessment System with Automatic Extraction of Event Types

NASA Astrophysics Data System (ADS)

Capet, Philippe; Delavallade, Thomas; Nakamura, Takuya; Sandor, Agnes; Tarsitano, Cedric; Voyatzi, Stavroula

In this article we describe the joint effort of experts in linguistics, information extraction and risk assessment to integrate EventSpotter, an automatic event extraction engine, into ADAC, an automated early warning system. By detecting as early as possible weak signals of emerging risks ADAC provides a dynamic synthetic picture of situations involving risk. The ADAC system calculates risk on the basis of fuzzy logic rules operated on a template graph whose leaves are event types. EventSpotter is based on a general purpose natural language dependency parser, XIP, enhanced with domain-specific lexical resources (Lexicon-Grammar). Its role is to automatically feed the leaves with input data.

Dependency distance: A new perspective on the syntactic development in second language acquisition. Comment on "Dependency distance: A new perspective on syntactic patterns in natural language" by Haitao Liu et al.

NASA Astrophysics Data System (ADS)

Jiang, Jingyang; Ouyang, Jinghui

2017-07-01

Liu et al. [1] offers a clear and informative account of the use of dependency distance in studying natural languages, with a focus on the viewpoint that dependency distance minimization (DDM) can be regarded as a linguistic universal. We would like to add the perspective of employing dependency distance in the studies of second languages acquisition (SLA), particularly the studies of syntactic development.

New Ways to Learn a Foreign Language.

ERIC Educational Resources Information Center

Hall, Robert A., Jr.

This text focuses on the nature of language learning in the light of modern linguistic analysis. Common linguistic problems encountered by students of eight major languages are examined--Latin, Greek, French, Spanish, Portuguese, Italian, German, and Russian. The text discusses the nature of language, building new language habits, overcoming…

DDM at Work: Reply to comments on "Dependency distance: A new perspective on syntactic patterns in natural languages".

PubMed

Xu, Chunshan; Liang, Junying; Liu, Haitao

2017-07-01

We provide responses to the commentaries in this volume to evaluate, clarify and extend some of the arguments in Dependency distance: A new perspective on syntactic patterns in natural languages. Evidences show that DDM (dependency distance minimization) is an important linguistic universal, biologically or cognitively motivated, in shaping the language system. As a general tendency, DDM works quite well in theoretical argumentations as well as practical applications. However, this does not mean that DDM is the only linguistic universal that works: it is highly possible that other factors, which might be biologically, physically, socially or culturally motivated, work as well to jointly mold languages. Copyright © 2017 Elsevier B.V. All rights reserved.

Improved P300 speller performance using electrocorticography, spectral features, and natural language processing.

PubMed

Speier, William; Fried, Itzhak; Pouratian, Nader

2013-07-01

The P300 speller is a system designed to restore communication to patients with advanced neuromuscular disorders. This study was designed to explore the potential improvement from using electrocorticography (ECoG) compared to the more traditional usage of electroencephalography (EEG). We tested the P300 speller on two epilepsy patients with temporary subdural electrode arrays over the occipital and temporal lobes respectively. We then performed offline analysis to determine the accuracy and bit rate of the system and integrated spectral features into the classifier and used a natural language processing (NLP) algorithm to further improve the results. The subject with the occipital grid achieved an accuracy of 82.77% and a bit rate of 41.02, which improved to 96.31% and 49.47 respectively using a language model and spectral features. The temporal grid patient achieved an accuracy of 59.03% and a bit rate of 18.26 with an improvement to 75.81% and 27.05 respectively using a language model and spectral features. Spatial analysis of the individual electrodes showed best performance using signals generated and recorded near the occipital pole. Using ECoG and integrating language information and spectral features can improve the bit rate of a P300 speller system. This improvement is sensitive to the electrode placement and likely depends on visually evoked potentials. This study shows that there can be an improvement in BCI performance when using ECoG, but that it is sensitive to the electrode location. Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

A Sibling-Mediated Intervention for Children with Autism Spectrum Disorder: Using the Natural Language Paradigm (NLP)

ERIC Educational Resources Information Center

Spector, Vicki; Charlop, Marjorie H.

2018-01-01

We taught three typically developing siblings to occasion speech by implementing the Natural Language Paradigm (NLP) with their brothers with autism spectrum disorder (ASD). A non-concurrent multiple baseline design across children with ASD and sibling dyads was used. Ancillary behaviors of happiness, play, and joint attention for the children…

Language of the Earth: Exploring Natural Hazards through a Literary Anthology

NASA Astrophysics Data System (ADS)

Malamud, B. D.; Rhodes, F. H. T.

2009-04-01

This paper explores natural hazards teaching and communications through the use of a literary anthology of writings about the earth aimed at non-experts. Teaching natural hazards in high-school and university introductory Earth Science and Geography courses revolves mostly around lectures, examinations, and laboratory demonstrations/activities. Often the results of such a course are that a student 'memorizes' the answers, and is penalized when they miss a given fact [e.g., "You lost one point because you were off by 50 km/hr on the wind speed of an F5 tornado."] Although facts and general methodologies are certainly important when teaching natural hazards, it is a strong motivation to a student's assimilation of, and enthusiasm for, this knowledge, if supplemented by writings about the Earth. In this paper, we discuss a literary anthology which we developed [Language of the Earth, Rhodes, Stone, Malamud, Wiley-Blackwell, 2008] which includes many descriptions about natural hazards. Using first- and second-hand accounts of landslides, earthquakes, tsunamis, floods and volcanic eruptions, through the writings of McPhee, Gaskill, Voltaire, Austin, Cloos, and many others, hazards become 'alive', and more than 'just' a compilation of facts and processes. Using short excerpts such as these, or other similar anthologies, of remarkably written accounts and discussions about natural hazards results in 'dry' facts becoming more than just facts. These often highly personal viewpoints of our catostrophic world, provide a useful supplement to a student's understanding of the turbulent world in which we live.

Conceptual Complexity and Apparent Contradictions in Mathematics Language

ERIC Educational Resources Information Center

Gough, John

2007-01-01

Mathematics is like a language, although technically it is not a natural or informal human language, but a formal, that is, artificially constructed language. Importantly, educators use their natural everyday language to teach the formal language of mathematics. At times, however, instructors encounter problems when the technical words they use,…

A Natural Language Intelligent Tutoring System for Training Pathologists - Implementation and Evaluation

PubMed Central

El Saadawi, Gilan M.; Tseytlin, Eugene; Legowski, Elizabeth; Jukic, Drazen; Castine, Melissa; Fine, Jeffrey; Gormley, Robert; Crowley, Rebecca S.

2009-01-01

Introduction We developed and evaluated a Natural Language Interface (NLI) for an Intelligent Tutoring System (ITS) in Diagnostic Pathology. The system teaches residents to examine pathologic slides and write accurate pathology reports while providing immediate feedback on errors they make in their slide review and diagnostic reports. Residents can ask for help at any point in the case, and will receive context-specific feedback. Research Questions We evaluated (1) the performance of our natural language system, (2) the effect of the system on learning (3) the effect of feedback timing on learning gains and (4) the effect of ReportTutor on performance to self-assessment correlations. Methods The study uses a crossover 2×2 factorial design. We recruited 20 subjects from 4 academic programs. Subjects were randomly assigned to one of the four conditions - two conditions for the immediate interface, and two for the delayed interface. An expert dermatopathologist created a reference standard and 2 board certified AP/CP pathology fellows manually coded the residents' assessment reports. Subjects were given the opportunity to self grade their performance and we used a survey to determine student response to both interfaces. Results Our results show a highly significant improvement in report writing after one tutoring session with 4-fold increase in the learning gains with both interfaces but no effect of feedback timing on performance gains. Residents who used the immediate feedback interface first experienced a feature learning gain that is correlated with the number of cases they viewed. There was no correlation between performance and self-assessment in either condition. PMID:17934789

A natural language intelligent tutoring system for training pathologists: implementation and evaluation.

PubMed

El Saadawi, Gilan M; Tseytlin, Eugene; Legowski, Elizabeth; Jukic, Drazen; Castine, Melissa; Fine, Jeffrey; Gormley, Robert; Crowley, Rebecca S

2008-12-01

We developed and evaluated a Natural Language Interface (NLI) for an Intelligent Tutoring System (ITS) in Diagnostic Pathology. The system teaches residents to examine pathologic slides and write accurate pathology reports while providing immediate feedback on errors they make in their slide review and diagnostic reports. Residents can ask for help at any point in the case, and will receive context-specific feedback. We evaluated (1) the performance of our natural language system, (2) the effect of the system on learning (3) the effect of feedback timing on learning gains and (4) the effect of ReportTutor on performance to self-assessment correlations. The study uses a crossover 2 x 2 factorial design. We recruited 20 subjects from 4 academic programs. Subjects were randomly assigned to one of the four conditions--two conditions for the immediate interface, and two for the delayed interface. An expert dermatopathologist created a reference standard and 2 board certified AP/CP pathology fellows manually coded the residents' assessment reports. Subjects were given the opportunity to self grade their performance and we used a survey to determine student response to both interfaces. Our results show a highly significant improvement in report writing after one tutoring session with 4-fold increase in the learning gains with both interfaces but no effect of feedback timing on performance gains. Residents who used the immediate feedback interface first experienced a feature learning gain that is correlated with the number of cases they viewed. There was no correlation between performance and self-assessment in either condition.

Teaching Language-Deviant Children to Generalize Newly Taught Language: A Socio-Ecological Approach. Volume I. Final Report.

ERIC Educational Resources Information Center

Schiefelbusch, R. L.; Rogers-Warren, Ann

The report examines longitudinal research on language generalization in natural environments of 32 severely retarded, moderately retarded, and mildly language delayed preschool children. All Ss received language training on one of two programs and Ss' speech samples in a natural environment were collected and analyzed for evidence of…

Natural language processing systems for capturing and standardizing unstructured clinical information: A systematic review.

PubMed

Kreimeyer, Kory; Foster, Matthew; Pandey, Abhishek; Arya, Nina; Halford, Gwendolyn; Jones, Sandra F; Forshee, Richard; Walderhaug, Mark; Botsis, Taxiarchis

2017-09-01

We followed a systematic approach based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses to identify existing clinical natural language processing (NLP) systems that generate structured information from unstructured free text. Seven literature databases were searched with a query combining the concepts of natural language processing and structured data capture. Two reviewers screened all records for relevance during two screening phases, and information about clinical NLP systems was collected from the final set of papers. A total of 7149 records (after removing duplicates) were retrieved and screened, and 86 were determined to fit the review criteria. These papers contained information about 71 different clinical NLP systems, which were then analyzed. The NLP systems address a wide variety of important clinical and research tasks. Certain tasks are well addressed by the existing systems, while others remain as open challenges that only a small number of systems attempt, such as extraction of temporal information or normalization of concepts to standard terminologies. This review has identified many NLP systems capable of processing clinical free text and generating structured output, and the information collected and evaluated here will be important for prioritizing development of new approaches for clinical NLP. Copyright © 2017 Elsevier Inc. All rights reserved.

The Two-Way Language Bridge: Co-Constructing Bilingual Language Learning Opportunities

ERIC Educational Resources Information Center

Martin-Beltran, Melinda

2010-01-01

Using a sociocultural theoretical lens, this study examines the nature of student interactions in a dual immersion school to analyze affordances for bilingual language learning, language exchange, and co-construction of language expertise. This article focuses on data from audio- and video-recorded interactions of fifth-grade students engaged in…

The Contemporary Thesaurus of Social Science Terms and Synonyms: A Guide for Natural Language Computer Searching.

ERIC Educational Resources Information Center

Knapp, Sara D., Comp.

This book is designed primarily to help users find meaningful words for natural language, or free-text, computer searching of bibliographic and textual databases in the social and behavioral sciences. Additionally, it covers many socially relevant and technical topics not covered by the usual literary thesaurus, therefore it may also be useful for…

Natural Language Processing Methods and Systems for Biomedical Ontology Learning

PubMed Central

Liu, Kaihong; Hogan, William R.; Crowley, Rebecca S.

2010-01-01

While the biomedical informatics community widely acknowledges the utility of domain ontologies, there remain many barriers to their effective use. One important requirement of domain ontologies is that they must achieve a high degree of coverage of the domain concepts and concept relationships. However, the development of these ontologies is typically a manual, time-consuming, and often error-prone process. Limited resources result in missing concepts and relationships as well as difficulty in updating the ontology as knowledge changes. Methodologies developed in the fields of natural language processing, information extraction, information retrieval and machine learning provide techniques for automating the enrichment of an ontology from free-text documents. In this article, we review existing methodologies and developed systems, and discuss how existing methods can benefit the development of biomedical ontologies. PMID:20647054

What can Natural Language Processing do for Clinical Decision Support?

PubMed Central

Demner-Fushman, Dina; Chapman, Wendy W.; McDonald, Clement J.

2009-01-01

Computerized Clinical Decision Support (CDS) aims to aid decision making of health care providers and the public by providing easily accessible health-related information at the point and time it is needed. Natural Language Processing (NLP) is instrumental in using free-text information to drive CDS, representing clinical knowledge and CDS interventions in standardized formats, and leveraging clinical narrative. The early innovative NLP research of clinical narrative was followed by a period of stable research conducted at the major clinical centers and a shift of mainstream interest to biomedical NLP. This review primarily focuses on the recently renewed interest in development of fundamental NLP methods and advances in the NLP systems for CDS. The current solutions to challenges posed by distinct sublanguages, intended user groups, and support goals are discussed. PMID:19683066

Beliefs about Language Learning in Study Abroad: Advocating for a Language Ideology Approach

ERIC Educational Resources Information Center

Surtees, Victoria

2016-01-01

Study Abroad (SA) has long enjoyed the unquestioning support of the general public, governments, and its benefits for language learning in many ways have been naturalized as "common sense" (Twombly et al., 2012). Language ideology scholars would say that this naturalization itself is indication that there are strong ideological forces at…

First Language Acquisition and Teaching

ERIC Educational Resources Information Center

Cruz-Ferreira, Madalena

2011-01-01

"First language acquisition" commonly means the acquisition of a single language in childhood, regardless of the number of languages in a child's natural environment. Language acquisition is variously viewed as predetermined, wondrous, a source of concern, and as developing through formal processes. "First language teaching" concerns schooling in…

Context Analysis of Customer Requests using a Hybrid Adaptive Neuro Fuzzy Inference System and Hidden Markov Models in the Natural Language Call Routing Problem

NASA Astrophysics Data System (ADS)

Rustamov, Samir; Mustafayev, Elshan; Clements, Mark A.

2018-04-01

The context analysis of customer requests in a natural language call routing problem is investigated in the paper. One of the most significant problems in natural language call routing is a comprehension of client request. With the aim of finding a solution to this issue, the Hybrid HMM and ANFIS models become a subject to an examination. Combining different types of models (ANFIS and HMM) can prevent misunderstanding by the system for identification of user intention in dialogue system. Based on these models, the hybrid system may be employed in various language and call routing domains due to nonusage of lexical or syntactic analysis in classification process.

Exploring the Ancestral Roots of American Sign Language: Lexical Borrowing from Cistercian Sign Language and French Sign Language

ERIC Educational Resources Information Center

Cagle, Keith Martin

2010-01-01

American Sign Language (ASL) is the natural and preferred language of the Deaf community in both the United States and Canada. Woodward (1978) estimated that approximately 60% of the ASL lexicon is derived from early 19th century French Sign Language, which is known as "langue des signes francaise" (LSF). The lexicon of LSF and ASL may…

Sentence Repetition in Deaf Children with Specific Language Impairment in British Sign Language

ERIC Educational Resources Information Center

Marshall, Chloë; Mason, Kathryn; Rowley, Katherine; Herman, Rosalind; Atkinson, Joanna; Woll, Bencie; Morgan, Gary

2015-01-01

Children with specific language impairment (SLI) perform poorly on sentence repetition tasks across different spoken languages, but until now, this methodology has not been investigated in children who have SLI in a signed language. Users of a natural sign language encode different sentence meanings through their choice of signs and by altering…

Computing Accurate Grammatical Feedback in a Virtual Writing Conference for German-Speaking Elementary-School Children: An Approach Based on Natural Language Generation

ERIC Educational Resources Information Center

Harbusch, Karin; Itsova, Gergana; Koch, Ulrich; Kuhner, Christine

2009-01-01

We built a natural language processing (NLP) system implementing a "virtual writing conference" for elementary-school children, with German as the target language. Currently, state-of-the-art computer support for writing tasks is restricted to multiple-choice questions or quizzes because automatic parsing of the often ambiguous and fragmentary…

Prediction During Natural Language Comprehension.

PubMed

Willems, Roel M; Frank, Stefan L; Nijhof, Annabel D; Hagoort, Peter; van den Bosch, Antal

2016-06-01

The notion of prediction is studied in cognitive neuroscience with increasing intensity. We investigated the neural basis of 2 distinct aspects of word prediction, derived from information theory, during story comprehension. We assessed the effect of entropy of next-word probability distributions as well as surprisal A computational model determined entropy and surprisal for each word in 3 literary stories. Twenty-four healthy participants listened to the same 3 stories while their brain activation was measured using fMRI. Reversed speech fragments were presented as a control condition. Brain areas sensitive to entropy were left ventral premotor cortex, left middle frontal gyrus, right inferior frontal gyrus, left inferior parietal lobule, and left supplementary motor area. Areas sensitive to surprisal were left inferior temporal sulcus ("visual word form area"), bilateral superior temporal gyrus, right amygdala, bilateral anterior temporal poles, and right inferior frontal sulcus. We conclude that prediction during language comprehension can occur at several levels of processing, including at the level of word form. Our study exemplifies the power of combining computational linguistics with cognitive neuroscience, and additionally underlines the feasibility of studying continuous spoken language materials with fMRI. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

From Web Directories to Ontologies: Natural Language Processing Challenges

NASA Astrophysics Data System (ADS)

Zaihrayeu, Ilya; Sun, Lei; Giunchiglia, Fausto; Pan, Wei; Ju, Qi; Chi, Mingmin; Huang, Xuanjing

Hierarchical classifications are used pervasively by humans as a means to organize their data and knowledge about the world. One of their main advantages is that natural language labels, used to describe their contents, are easily understood by human users. However, at the same time, this is also one of their main disadvantages as these same labels are ambiguous and very hard to be reasoned about by software agents. This fact creates an insuperable hindrance for classifications to being embedded in the Semantic Web infrastructure. This paper presents an approach to converting classifications into lightweight ontologies, and it makes the following contributions: (i) it identifies the main NLP problems related to the conversion process and shows how they are different from the classical problems of NLP; (ii) it proposes heuristic solutions to these problems, which are especially effective in this domain; and (iii) it evaluates the proposed solutions by testing them on DMoz data.

Natural Language Processing Of Online Propaganda As A Means Of Passively Monitoring An Adversarial Ideology

DTIC Science & Technology

2017-03-01

Warfare. 14. SUBJECT TERMS data mining, natural language processing, machine learning, algorithm design , information warfare, propaganda 15. NUMBER OF...Speech Tags. Adapted from [12]. CC Coordinating conjunction PRP$ Possessive pronoun CD Cardinal number RB Adverb DT Determiner RBR Adverb, comparative ... comparative UH Interjection JJS Adjective, superlative VB Verb, base form LS List item marker VBD Verb, past tense MD Modal VBG Verb, gerund or

The Effect of Input Device on User Performance With a Menu-Based Natural Language Interface

DTIC Science & Technology

1988-01-01

Texas. The experiment was conducted and the data were analyzed by Virginia Polytechnic Institute and State University human factors engineexing personnel...comments. Thanks to Dr. William Fisher for his help in the parsing of the grammar used in the MBNL interface prototype, and to Mr. Ken Stevenson for...natural language instructions to accomplish particular tasks (Bobrow & Collins, 1975; Brown, Burton, & Bell, 1975; Ford, 1981; Green, Wolf, Chomsky

A UMLS-based spell checker for natural language processing in vaccine safety.

PubMed

Tolentino, Herman D; Matters, Michael D; Walop, Wikke; Law, Barbara; Tong, Wesley; Liu, Fang; Fontelo, Paul; Kohl, Katrin; Payne, Daniel C

2007-02-12

The Institute of Medicine has identified patient safety as a key goal for health care in the United States. Detecting vaccine adverse events is an important public health activity that contributes to patient safety. Reports about adverse events following immunization (AEFI) from surveillance systems contain free-text components that can be analyzed using natural language processing. To extract Unified Medical Language System (UMLS) concepts from free text and classify AEFI reports based on concepts they contain, we first needed to clean the text by expanding abbreviations and shortcuts and correcting spelling errors. Our objective in this paper was to create a UMLS-based spelling error correction tool as a first step in the natural language processing (NLP) pipeline for AEFI reports. We developed spell checking algorithms using open source tools. We used de-identified AEFI surveillance reports to create free-text data sets for analysis. After expansion of abbreviated clinical terms and shortcuts, we performed spelling correction in four steps: (1) error detection, (2) word list generation, (3) word list disambiguation and (4) error correction. We then measured the performance of the resulting spell checker by comparing it to manual correction. We used 12,056 words to train the spell checker and tested its performance on 8,131 words. During testing, sensitivity, specificity, and positive predictive value (PPV) for the spell checker were 74% (95% CI: 74-75), 100% (95% CI: 100-100), and 47% (95% CI: 46%-48%), respectively. We created a prototype spell checker that can be used to process AEFI reports. We used the UMLS Specialist Lexicon as the primary source of dictionary terms and the WordNet lexicon as a secondary source. We used the UMLS as a domain-specific source of dictionary terms to compare potentially misspelled words in the corpus. The prototype sensitivity was comparable to currently available tools, but the specificity was much superior. The slow processing

A UMLS-based spell checker for natural language processing in vaccine safety

PubMed Central

Tolentino, Herman D; Matters, Michael D; Walop, Wikke; Law, Barbara; Tong, Wesley; Liu, Fang; Fontelo, Paul; Kohl, Katrin; Payne, Daniel C

2007-01-01

Background The Institute of Medicine has identified patient safety as a key goal for health care in the United States. Detecting vaccine adverse events is an important public health activity that contributes to patient safety. Reports about adverse events following immunization (AEFI) from surveillance systems contain free-text components that can be analyzed using natural language processing. To extract Unified Medical Language System (UMLS) concepts from free text and classify AEFI reports based on concepts they contain, we first needed to clean the text by expanding abbreviations and shortcuts and correcting spelling errors. Our objective in this paper was to create a UMLS-based spelling error correction tool as a first step in the natural language processing (NLP) pipeline for AEFI reports. Methods We developed spell checking algorithms using open source tools. We used de-identified AEFI surveillance reports to create free-text data sets for analysis. After expansion of abbreviated clinical terms and shortcuts, we performed spelling correction in four steps: (1) error detection, (2) word list generation, (3) word list disambiguation and (4) error correction. We then measured the performance of the resulting spell checker by comparing it to manual correction. Results We used 12,056 words to train the spell checker and tested its performance on 8,131 words. During testing, sensitivity, specificity, and positive predictive value (PPV) for the spell checker were 74% (95% CI: 74–75), 100% (95% CI: 100–100), and 47% (95% CI: 46%–48%), respectively. Conclusion We created a prototype spell checker that can be used to process AEFI reports. We used the UMLS Specialist Lexicon as the primary source of dictionary terms and the WordNet lexicon as a secondary source. We used the UMLS as a domain-specific source of dictionary terms to compare potentially misspelled words in the corpus. The prototype sensitivity was comparable to currently available tools, but the

A study of the very high order natural user language (with AI capabilities) for the NASA space station common module

NASA Technical Reports Server (NTRS)

Gill, E. N.

1986-01-01

The requirements are identified for a very high order natural language to be used by crew members on board the Space Station. The hardware facilities, databases, realtime processes, and software support are discussed. The operations and capabilities that will be required in both normal (routine) and abnormal (nonroutine) situations are evaluated. A structure and syntax for an interface (front-end) language to satisfy the above requirements are recommended.

Modeling Memory for Language Understanding.

DTIC Science & Technology

1982-02-01

Abstract Research on natural language understanding by computer has shown that the nature and organization of memory plays j central role in the...block number) Research on natural language understanding by computer has shown that the nature and organization of memory plays a central role in the...understanding mechanism. Further we claim that such reminding is at the root of how we learn. Issues such as these have played an important part in shaping the

Prediction of Emergency Department Hospital Admission Based on Natural Language Processing and Neural Networks.

PubMed

Zhang, Xingyu; Kim, Joyce; Patzer, Rachel E; Pitts, Stephen R; Patzer, Aaron; Schrager, Justin D

2017-10-26

To describe and compare logistic regression and neural network modeling strategies to predict hospital admission or transfer following initial presentation to Emergency Department (ED) triage with and without the addition of natural language processing elements. Using data from the National Hospital Ambulatory Medical Care Survey (NHAMCS), a cross-sectional probability sample of United States EDs from 2012 and 2013 survey years, we developed several predictive models with the outcome being admission to the hospital or transfer vs. discharge home. We included patient characteristics immediately available after the patient has presented to the ED and undergone a triage process. We used this information to construct logistic regression (LR) and multilayer neural network models (MLNN) which included natural language processing (NLP) and principal component analysis from the patient's reason for visit. Ten-fold cross validation was used to test the predictive capacity of each model and receiver operating curves (AUC) were then calculated for each model. Of the 47,200 ED visits from 642 hospitals, 6,335 (13.42%) resulted in hospital admission (or transfer). A total of 48 principal components were extracted by NLP from the reason for visit fields, which explained 75% of the overall variance for hospitalization. In the model including only structured variables, the AUC was 0.824 (95% CI 0.818-0.830) for logistic regression and 0.823 (95% CI 0.817-0.829) for MLNN. Models including only free-text information generated AUC of 0.742 (95% CI 0.731- 0.753) for logistic regression and 0.753 (95% CI 0.742-0.764) for MLNN. When both structured variables and free text variables were included, the AUC reached 0.846 (95% CI 0.839-0.853) for logistic regression and 0.844 (95% CI 0.836-0.852) for MLNN. The predictive accuracy of hospital admission or transfer for patients who presented to ED triage overall was good, and was improved with the inclusion of free text data from a patient

Teaching Mathematics with Intelligent Support in Natural Language. Tertiary Education Students Working with Parametrized Modelling Activities

ERIC Educational Resources Information Center

Rojano, Teresa; García-Campos, Montserrat

2017-01-01

This article reports the outcomes of a study that seeks to investigate the role of feedback, by way of an intelligent support system in natural language, in parametrized modelling activities carried out by a group of tertiary education students. With such a system, it is possible to simultaneously display on a computer screen a dialogue window and…

Cultural Perspectives Toward Language Learning

ERIC Educational Resources Information Center

Lin, Li-Li

2008-01-01

Cultural conflicts may be derived from using inappropriate language. Appropriate linguistic-pragmatic competence may also be produced by providing various and multicultural backgrounds. Culture and language are linked together naturally, unconsciously, and closely in daily social lives. Culture affects language and language affects culture through…

Natural Language Processing Accurately Calculates Adenoma and Sessile Serrated Polyp Detection Rates.

PubMed

Nayor, Jennifer; Borges, Lawrence F; Goryachev, Sergey; Gainer, Vivian S; Saltzman, John R

2018-07-01

ADR is a widely used colonoscopy quality indicator. Calculation of ADR is labor-intensive and cumbersome using current electronic medical databases. Natural language processing (NLP) is a method used to extract meaning from unstructured or free text data. (1) To develop and validate an accurate automated process for calculation of adenoma detection rate (ADR) and serrated polyp detection rate (SDR) on data stored in widely used electronic health record systems, specifically Epic electronic health record system, Provation ® endoscopy reporting system, and Sunquest PowerPath pathology reporting system. Screening colonoscopies performed between June 2010 and August 2015 were identified using the Provation ® reporting tool. An NLP pipeline was developed to identify adenomas and sessile serrated polyps (SSPs) on pathology reports corresponding to these colonoscopy reports. The pipeline was validated using a manual search. Precision, recall, and effectiveness of the natural language processing pipeline were calculated. ADR and SDR were then calculated. We identified 8032 screening colonoscopies that were linked to 3821 pathology reports (47.6%). The NLP pipeline had an accuracy of 100% for adenomas and 100% for SSPs. Mean total ADR was 29.3% (range 14.7-53.3%); mean male ADR was 35.7% (range 19.7-62.9%); and mean female ADR was 24.9% (range 9.1-51.0%). Mean total SDR was 4.0% (0-9.6%). We developed and validated an NLP pipeline that accurately and automatically calculates ADRs and SDRs using data stored in Epic, Provation ® and Sunquest PowerPath. This NLP pipeline can be used to evaluate colonoscopy quality parameters at both individual and practice levels.

CLAMP - a toolkit for efficiently building customized clinical natural language processing pipelines.

PubMed

Soysal, Ergin; Wang, Jingqi; Jiang, Min; Wu, Yonghui; Pakhomov, Serguei; Liu, Hongfang; Xu, Hua

2017-11-24

Existing general clinical natural language processing (NLP) systems such as MetaMap and Clinical Text Analysis and Knowledge Extraction System have been successfully applied to information extraction from clinical text. However, end users often have to customize existing systems for their individual tasks, which can require substantial NLP skills. Here we present CLAMP (Clinical Language Annotation, Modeling, and Processing), a newly developed clinical NLP toolkit that provides not only state-of-the-art NLP components, but also a user-friendly graphic user interface that can help users quickly build customized NLP pipelines for their individual applications. Our evaluation shows that the CLAMP default pipeline achieved good performance on named entity recognition and concept encoding. We also demonstrate the efficiency of the CLAMP graphic user interface in building customized, high-performance NLP pipelines with 2 use cases, extracting smoking status and lab test values. CLAMP is publicly available for research use, and we believe it is a unique asset for the clinical NLP community. © The Author 2017. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Intelligent Performance Analysis with a Natural Language Interface

NASA Astrophysics Data System (ADS)

Juuso, Esko K.

2017-09-01

Performance improvement is taken as the primary goal in the asset management. Advanced data analysis is needed to efficiently integrate condition monitoring data into the operation and maintenance. Intelligent stress and condition indices have been developed for control and condition monitoring by combining generalized norms with efficient nonlinear scaling. These nonlinear scaling methodologies can also be used to handle performance measures used for management since management oriented indicators can be presented in the same scale as intelligent condition and stress indices. Performance indicators are responses of the process, machine or system to the stress contributions analyzed from process and condition monitoring data. Scaled values are directly used in intelligent temporal analysis to calculate fluctuations and trends. All these methodologies can be used in prognostics and fatigue prediction. The meanings of the variables are beneficial in extracting expert knowledge and representing information in natural language. The idea of dividing the problems into the variable specific meanings and the directions of interactions provides various improvements for performance monitoring and decision making. The integrated temporal analysis and uncertainty processing facilitates the efficient use of domain expertise. Measurements can be monitored with generalized statistical process control (GSPC) based on the same scaling functions.

Language discrimination without language: Experiments on tamarin monkeys

NASA Astrophysics Data System (ADS)

Tincoff, Ruth; Hauser, Marc; Spaepen, Geertrui; Tsao, Fritz; Mehler, Jacques

2002-05-01

Human newborns can discriminate spoken languages differing on prosodic characteristics such as the timing of rhythmic units [T. Nazzi et al., JEP:HPP 24, 756-766 (1998)]. Cotton-top tamarins have also demonstrated a similar ability to discriminate a morae- (Japanese) vs a stress-timed (Dutch) language [F. Ramus et al., Science 288, 349-351 (2000)]. The finding that tamarins succeed in this task when either natural or synthesized utterances are played in a forward direction, but fail on backward utterances which disrupt the rhythmic cues, suggests that sensitivity to language rhythm may rely on general processes of the primate auditory system. However, the rhythm hypothesis also predicts that tamarins would fail to discriminate languages from the same rhythm class, such as English and Dutch. To assess the robustness of this ability, tamarins were tested on a different-rhythm-class distinction, Polish vs Japanese, and a new same-rhythm-class distinction, English vs Dutch. The stimuli were natural forward utterances produced by multiple speakers. As predicted by the rhythm hypothesis, tamarins discriminated between Polish and Japanese, but not English and Dutch. These findings strengthen the claim that discriminating the rhythmic cues of language does not require mechanisms specialized for human speech. [Work supported by NSF.

Crowdsourcing a Normative Natural Language Dataset: A Comparison of Amazon Mechanical Turk and In-Lab Data Collection

PubMed Central

Bex, Peter J; Woods, Russell L

2013-01-01

Background Crowdsourcing has become a valuable method for collecting medical research data. This approach, recruiting through open calls on the Web, is particularly useful for assembling large normative datasets. However, it is not known how natural language datasets collected over the Web differ from those collected under controlled laboratory conditions. Objective To compare the natural language responses obtained from a crowdsourced sample of participants with responses collected in a conventional laboratory setting from participants recruited according to specific age and gender criteria. Methods We collected natural language descriptions of 200 half-minute movie clips, from Amazon Mechanical Turk workers (crowdsourced) and 60 participants recruited from the community (lab-sourced). Crowdsourced participants responded to as many clips as they wanted and typed their responses, whereas lab-sourced participants gave spoken responses to 40 clips, and their responses were transcribed. The content of the responses was evaluated using a take-one-out procedure, which compared responses to other responses to the same clip and to other clips, with a comparison of the average number of shared words. Results In contrast to the 13 months of recruiting that was required to collect normative data from 60 lab-sourced participants (with specific demographic characteristics), only 34 days were needed to collect normative data from 99 crowdsourced participants (contributing a median of 22 responses). The majority of crowdsourced workers were female, and the median age was 35 years, lower than the lab-sourced median of 62 years but similar to the median age of the US population. The responses contributed by the crowdsourced participants were longer on average, that is, 33 words compared to 28 words (P<.001), and they used a less varied vocabulary. However, there was strong similarity in the words used to describe a particular clip between the two datasets, as a cross-dataset count

Evolution: Language Use and the Evolution of Languages

NASA Astrophysics Data System (ADS)

Croft, William

Language change can be understood as an evolutionary process. Language change occurs at two different timescales, corresponding to the two steps of the evolutionary process. The first timescale is very short, namely, the production of an utterance: this is where linguistic structures are replicated and language variation is generated. The second timescale is (or can be) very long, namely, the propagation of linguistic variants in the speech community: this is where certain variants are selected over others. At both timescales, the evolutionary process is driven by social interaction and the role language plays in it. An understanding of social interaction at the micro-level—face-to-face interactions—and at the macro-level—the structure of speech communities—gives us the basis for understanding the generation and propagation of language structures, and understanding the nature of language itself.

Knowledge-based machine indexing from natural language text: Knowledge base design, development, and maintenance

NASA Technical Reports Server (NTRS)

Genuardi, Michael T.

1993-01-01

One strategy for machine-aided indexing (MAI) is to provide a concept-level analysis of the textual elements of documents or document abstracts. In such systems, natural-language phrases are analyzed in order to identify and classify concepts related to a particular subject domain. The overall performance of these MAI systems is largely dependent on the quality and comprehensiveness of their knowledge bases. These knowledge bases function to (1) define the relations between a controlled indexing vocabulary and natural language expressions; (2) provide a simple mechanism for disambiguation and the determination of relevancy; and (3) allow the extension of concept-hierarchical structure to all elements of the knowledge file. After a brief description of the NASA Machine-Aided Indexing system, concerns related to the development and maintenance of MAI knowledge bases are discussed. Particular emphasis is given to statistically-based text analysis tools designed to aid the knowledge base developer. One such tool, the Knowledge Base Building (KBB) program, presents the domain expert with a well-filtered list of synonyms and conceptually-related phrases for each thesaurus concept. Another tool, the Knowledge Base Maintenance (KBM) program, functions to identify areas of the knowledge base affected by changes in the conceptual domain (for example, the addition of a new thesaurus term). An alternate use of the KBM as an aid in thesaurus construction is also discussed.

Efficient Queries of Stand-off Annotations for Natural Language Processing on Electronic Medical Records.

PubMed

Luo, Yuan; Szolovits, Peter

2016-01-01

In natural language processing, stand-off annotation uses the starting and ending positions of an annotation to anchor it to the text and stores the annotation content separately from the text. We address the fundamental problem of efficiently storing stand-off annotations when applying natural language processing on narrative clinical notes in electronic medical records (EMRs) and efficiently retrieving such annotations that satisfy position constraints. Efficient storage and retrieval of stand-off annotations can facilitate tasks such as mapping unstructured text to electronic medical record ontologies. We first formulate this problem into the interval query problem, for which optimal query/update time is in general logarithm. We next perform a tight time complexity analysis on the basic interval tree query algorithm and show its nonoptimality when being applied to a collection of 13 query types from Allen's interval algebra. We then study two closely related state-of-the-art interval query algorithms, proposed query reformulations, and augmentations to the second algorithm. Our proposed algorithm achieves logarithmic time stabbing-max query time complexity and solves the stabbing-interval query tasks on all of Allen's relations in logarithmic time, attaining the theoretic lower bound. Updating time is kept logarithmic and the space requirement is kept linear at the same time. We also discuss interval management in external memory models and higher dimensions.

Efficient Queries of Stand-off Annotations for Natural Language Processing on Electronic Medical Records

PubMed Central

Luo, Yuan; Szolovits, Peter

2016-01-01

In natural language processing, stand-off annotation uses the starting and ending positions of an annotation to anchor it to the text and stores the annotation content separately from the text. We address the fundamental problem of efficiently storing stand-off annotations when applying natural language processing on narrative clinical notes in electronic medical records (EMRs) and efficiently retrieving such annotations that satisfy position constraints. Efficient storage and retrieval of stand-off annotations can facilitate tasks such as mapping unstructured text to electronic medical record ontologies. We first formulate this problem into the interval query problem, for which optimal query/update time is in general logarithm. We next perform a tight time complexity analysis on the basic interval tree query algorithm and show its nonoptimality when being applied to a collection of 13 query types from Allen’s interval algebra. We then study two closely related state-of-the-art interval query algorithms, proposed query reformulations, and augmentations to the second algorithm. Our proposed algorithm achieves logarithmic time stabbing-max query time complexity and solves the stabbing-interval query tasks on all of Allen’s relations in logarithmic time, attaining the theoretic lower bound. Updating time is kept logarithmic and the space requirement is kept linear at the same time. We also discuss interval management in external memory models and higher dimensions. PMID:27478379

The Tao of Whole Language.

ERIC Educational Resources Information Center

Zola, Meguido

1989-01-01

Uses the philosophy of Taoism as a metaphor in describing the whole language approach to language arts instruction. The discussion covers the key principles that inform the whole language approach, the resulting holistic nature of language programs, and the role of the teacher in this approach. (16 references) (CLB)

Language as a Liberal Art.

ERIC Educational Resources Information Center

Stein, Jack M.

Language, considered as a liberal art, is examined in the light of other philosophical viewpoints concerning the nature of language in relation to second language instruction in this paper. Critical of an earlier mechanistic audio-lingual learning theory, translation approaches to language learning, vocabulary list-oriented courses, graduate…

Theoretical Studies in Natural Language Understanding.

DTIC Science & Technology

1980-05-01

Contract Expiration Date: 1 May 1977 30 April 1981 Short Title of Work: Scientific Officer: Language Understanding Marvin Denicoff [ Report No. 4395 Bolt...Cambridge, MA 02138, October (more extensive than the Quillian 1968 paper by the same name). Quillian, M.R. 1968. "Semantic Memory," in M. Minsky (ed

Building pathway graphs from BioPAX data in R.

PubMed

Benis, Nirupama; Schokker, Dirkjan; Kramer, Frank; Smits, Mari A; Suarez-Diez, Maria

2016-01-01

Biological pathways are increasingly available in the BioPAX format which uses an RDF model for data storage. One can retrieve the information in this data model in the scripting language R using the package rBiopaxParser , which converts the BioPAX format to one readable in R. It also has a function to build a regulatory network from the pathway information. Here we describe an extension of this function. The new function allows the user to build graphs of entire pathways, including regulated as well as non-regulated elements, and therefore provides a maximum of information. This function is available as part of the rBiopaxParser distribution from Bioconductor.

Solving LR Conflicts Through Context Aware Scanning

NASA Astrophysics Data System (ADS)

Leon, C. Rodriguez; Forte, L. Garcia

2011-09-01

This paper presents a new algorithm to compute the exact list of tokens expected by any LR syntax analyzer at any point of the scanning process. The lexer can, at any time, compute the exact list of valid tokens to return only tokens in this set. In the case than more than one matching token is in the valid set, the lexer can resort to a nested LR parser to disambiguate. Allowing nested LR parsing requires some slight modifications when building the LR parsing tables. We also show how LR parsers can parse conflictive and inherently ambiguous languages using a combination of nested parsing and context aware scanning. These expanded lexical analyzers can be generated from high level specifications.

Of Substance: The Nature of Language Effects on Entity Construal

PubMed Central

Li, Peggy; Dunham, Yarrow; Carey, Susan

2009-01-01

Shown an entity (e.g., a plastic whisk) labeled by a novel noun in neutral syntax, speakers of Japanese, a classifier language, are more likely to assume the noun refers to the substance (plastic) than are speakers of English, a count/mass language, who are instead more likely to assume it refers to the object kind (whisk; Imai and Gentner, 1997). Five experiments replicated this language type effect on entity construal, extended it to quite different stimuli from those studied before, and extended it to a comparison between Mandarin-speakers and English-speakers. A sixth experiment, which did not involve interpreting the meaning of a noun or a pronoun that stands for a noun, failed to find any effect of language type on entity construal. Thus, the overall pattern of findings supports a non-Whorfian, language on language account, according to which sensitivity to lexical statistics in a count/mass language leads adults to assign a novel noun in neutral syntax the status of a count noun, influencing construal of ambiguous entities. The experiments also document and explore cross-linguistically universal factors that influence entity construal, and favor Prasada's (1999) hypothesis that features indicating non-accidentalness of an entity's form lead participants to a construal of object-kind rather than substance-kind. Finally, the experiments document the age at which the language type effect emerges in lexical projection. The details of the developmental pattern are consistent with the lexical statistics hypothesis, along with a universal increase in sensitivity to material kind. PMID:19230873

Wikipedia and medicine: quantifying readership, editors, and the significance of natural language.

PubMed

Heilman, James M; West, Andrew G

2015-03-04

Wikipedia is a collaboratively edited encyclopedia. One of the most popular websites on the Internet, it is known to be a frequently used source of health care information by both professionals and the lay public. This paper quantifies the production and consumption of Wikipedia's medical content along 4 dimensions. First, we measured the amount of medical content in both articles and bytes and, second, the citations that supported that content. Third, we analyzed the medical readership against that of other health care websites between Wikipedia's natural language editions and its relationship with disease prevalence. Fourth, we surveyed the quantity/characteristics of Wikipedia's medical contributors, including year-over-year participation trends and editor demographics. Using a well-defined categorization infrastructure, we identified medically pertinent English-language Wikipedia articles and links to their foreign language equivalents. With these, Wikipedia can be queried to produce metadata and full texts for entire article histories. Wikipedia also makes available hourly reports that aggregate reader traffic at per-article granularity. An online survey was used to determine the background of contributors. Standard mining and visualization techniques (eg, aggregation queries, cumulative distribution functions, and/or correlation metrics) were applied to each of these datasets. Analysis focused on year-end 2013, but historical data permitted some longitudinal analysis. Wikipedia's medical content (at the end of 2013) was made up of more than 155,000 articles and 1 billion bytes of text across more than 255 languages. This content was supported by more than 950,000 references. Content was viewed more than 4.88 billion times in 2013. This makes it one of if not the most viewed medical resource(s) globally. The core editor community numbered less than 300 and declined over the past 5 years. The members of this community were half health care providers and 85

Autistic Symptomatology and Language Ability in Autism Spectrum Disorder and Specific Language Impairment

ERIC Educational Resources Information Center

Loucas, Tom; Charman, Tony; Pickles, Andrew; Simonoff, Emily; Chandler, Susie; Meldrum, David; Baird, Gillian

2008-01-01

Background: Autism spectrum disorders (ASD) and specific language impairment (SLI) are common developmental disorders characterised by deficits in language and communication. The nature of the relationship between them continues to be a matter of debate. This study investigates whether the co-occurrence of ASD and language impairment is associated…

MetaJC++: A flexible and automatic program transformation technique using meta framework

NASA Astrophysics Data System (ADS)

Beevi, Nadera S.; Reghu, M.; Chitraprasad, D.; Vinodchandra, S. S.

2014-09-01

Compiler is a tool to translate abstract code containing natural language terms to machine code. Meta compilers are available to compile more than one languages. We have developed a meta framework intends to combine two dissimilar programming languages, namely C++ and Java to provide a flexible object oriented programming platform for the user. Suitable constructs from both the languages have been combined, thereby forming a new and stronger Meta-Language. The framework is developed using the compiler writing tools, Flex and Yacc to design the front end of the compiler. The lexer and parser have been developed to accommodate the complete keyword set and syntax set of both the languages. Two intermediate representations have been used in between the translation of the source program to machine code. Abstract Syntax Tree has been used as a high level intermediate representation that preserves the hierarchical properties of the source program. A new machine-independent stack-based byte-code has also been devised to act as a low level intermediate representation. The byte-code is essentially organised into an output class file that can be used to produce an interpreted output. The results especially in the spheres of providing C++ concepts in Java have given an insight regarding the potential strong features of the resultant meta-language.

jmzReader: A Java parser library to process and visualize multiple text and XML-based mass spectrometry data formats.

PubMed

Griss, Johannes; Reisinger, Florian; Hermjakob, Henning; Vizcaíno, Juan Antonio

2012-03-01

We here present the jmzReader library: a collection of Java application programming interfaces (APIs) to parse the most commonly used peak list and XML-based mass spectrometry (MS) data formats: DTA, MS2, MGF, PKL, mzXML, mzData, and mzML (based on the already existing API jmzML). The library is optimized to be used in conjunction with mzIdentML, the recently released standard data format for reporting protein and peptide identifications, developed by the HUPO proteomics standards initiative (PSI). mzIdentML files do not contain spectra data but contain references to different kinds of external MS data files. As a key functionality, all parsers implement a common interface that supports the various methods used by mzIdentML to reference external spectra. Thus, when developing software for mzIdentML, programmers no longer have to support multiple MS data file formats but only this one interface. The library (which includes a viewer) is open source and, together with detailed documentation, can be downloaded from http://code.google.com/p/jmzreader/. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

RLL-1: A Representation Language Language

DTIC Science & Technology

1980-10-01

adaptable organisms over those which contain, built-in optimized features. Compare the extinct dinosaur , unable to adapt to new situations, with two of...natural language understandirq for KRL [Bobrow & Winograd] and OWL [Szolovits, et alD. For this reason , his language is ofL.:n inadequate for any...for no particular reason , switch the organ into its Oboe state. That is, the sequence which triggers a change to the organ is a Punction of the organ’s

How many kinds of reasoning? Inference, probability, and natural language semantics.

PubMed

Lassiter, Daniel; Goodman, Noah D

2015-03-01

The "new paradigm" unifying deductive and inductive reasoning in a Bayesian framework (Oaksford & Chater, 2007; Over, 2009) has been claimed to be falsified by results which show sharp differences between reasoning about necessity vs. plausibility (Heit & Rotello, 2010; Rips, 2001; Rotello & Heit, 2009). We provide a probabilistic model of reasoning with modal expressions such as "necessary" and "plausible" informed by recent work in formal semantics of natural language, and show that it predicts the possibility of non-linear response patterns which have been claimed to be problematic. Our model also makes a strong monotonicity prediction, while two-dimensional theories predict the possibility of reversals in argument strength depending on the modal word chosen. Predictions were tested using a novel experimental paradigm that replicates the previously-reported response patterns with a minimal manipulation, changing only one word of the stimulus between conditions. We found a spectrum of reasoning "modes" corresponding to different modal words, and strong support for our model's monotonicity prediction. This indicates that probabilistic approaches to reasoning can account in a clear and parsimonious way for data previously argued to falsify them, as well as new, more fine-grained, data. It also illustrates the importance of careful attention to the semantics of language employed in reasoning experiments. Copyright © 2014 Elsevier B.V. All rights reserved.

"Homo Pedagogicus": The Evolutionary Nature of Second Language Teaching

ERIC Educational Resources Information Center

Atkinson, Dwight

2017-01-01

Second language (SL) teacher educators tirelessly teach others how to teach. But how often do we actually define teaching? Without explicit definitional activity on this fundamental concept in second language teaching (SLT), it remains implicit and intuitive--the opposite of clear, productive understanding. I therefore explore the question,…

Integrated verification and testing system (IVTS) for HAL/S programs

NASA Technical Reports Server (NTRS)

Senn, E. H.; Ames, K. R.; Smith, K. A.

1983-01-01

The IVTS is a large software system designed to support user-controlled verification analysis and testing activities for programs written in the HAL/S language. The system is composed of a user interface and user command language, analysis tools and an organized data base of host system files. The analysis tools are of four major types: (1) static analysis, (2) symbolic execution, (3) dynamic analysis (testing), and (4) documentation enhancement. The IVTS requires a split HAL/S compiler, divided at the natural separation point between the parser/lexical analyzer phase and the target machine code generator phase. The IVTS uses the internal program form (HALMAT) between these two phases as primary input for the analysis tools. The dynamic analysis component requires some way to 'execute' the object HAL/S program. The execution medium may be an interpretive simulation or an actual host or target machine.

Epidemiology of angina pectoris: role of natural language processing of the medical record

PubMed Central

Pakhomov, Serguei; Hemingway, Harry; Weston, Susan A.; Jacobsen, Steven J.; Rodeheffer, Richard; Roger, Véronique L.

2007-01-01

Background The diagnosis of angina is challenging as it relies on symptom descriptions. Natural language processing (NLP) of the electronic medical record (EMR) can provide access to such information contained in free text that may not be fully captured by conventional diagnostic coding. Objective To test the hypothesis that NLP of the EMR improves angina pectoris (AP) ascertainment over diagnostic codes. Methods Billing records of in- and out-patients were searched for ICD-9 codes for AP, chronic ischemic heart disease and chest pain. EMR clinical reports were searched electronically for 50 specific non-negated natural language synonyms to these ICD-9 codes. The two methods were compared to a standardized assessment of angina by Rose questionnaire for three diagnostic levels: unspecified chest pain, exertional chest pain, and Rose angina. Results Compared to the Rose questionnaire, the true positive rate of EMR-NLP for unspecified chest pain was 62% (95%CI:55–67) vs. 51% (95%CI:44–58) for diagnostic codes (p<0.001). For exertional chest pain, the EMR-NLP true positive rate was 71% (95%CI:61–80) vs. 62% (95%CI:52–73) for diagnostic codes (p=0.10). Both approaches had 88% (95%CI:65–100) true positive rate for Rose angina. The EMR-NLP method consistently identified more patients with exertional chest pain over 28-month follow-up. Conclusion EMR-NLP method improves the detection of unspecified and exertional chest pain cases compared to diagnostic codes. These findings have implications for epidemiological and clinical studies of angina pectoris. PMID:17383310

Gendered Language in Interactive Discourse

ERIC Educational Resources Information Center

Hussey, Karen A.; Katz, Albert N.; Leith, Scott A.

2015-01-01

Over two studies, we examined the nature of gendered language in interactive discourse. In the first study, we analyzed gendered language from a chat corpus to see whether tokens of gendered language proposed in the gender-as-culture hypothesis (Maltz and Borker in "Language and social identity." Cambridge University Press, Cambridge, pp…

Automatic Lung-RADS™ classification with a natural language processing system.

PubMed

Beyer, Sebastian E; McKee, Brady J; Regis, Shawn M; McKee, Andrea B; Flacke, Sebastian; El Saadawi, Gilan; Wald, Christoph

2017-09-01

Our aim was to train a natural language processing (NLP) algorithm to capture imaging characteristics of lung nodules reported in a structured CT report and suggest the applicable Lung-RADS™ (LR) category. Our study included structured, clinical reports of consecutive CT lung screening (CTLS) exams performed from 08/2014 to 08/2015 at an ACR accredited Lung Cancer Screening Center. All patients screened were at high-risk for lung cancer according to the NCCN Guidelines ® . All exams were interpreted by one of three radiologists credentialed to read CTLS exams using LR using a standard reporting template. Training and test sets consisted of consecutive exams. Lung screening exams were divided into two groups: three training sets (500, 120, and 383 reports each) and one final evaluation set (498 reports). NLP algorithm results were compared with the gold standard of LR category assigned by the radiologist. The sensitivity/specificity of the NLP algorithm to correctly assign LR categories for suspicious nodules (LR 4) and positive nodules (LR 3/4) were 74.1%/98.6% and 75.0%/98.8% respectively. The majority of mismatches occurred in cases where pulmonary findings were present not currently addressed by LR. Misclassifications also resulted from the failure to identify exams as follow-up and the failure to completely characterize part-solid nodules. In a sub-group analysis among structured reports with standardized language, the sensitivity and specificity to detect LR 4 nodules were 87.0% and 99.5%, respectively. An NLP system can accurately suggest the appropriate LR category from CTLS exam findings when standardized reporting is used.

What baboons can (not) tell us about natural language grammars.

PubMed

Poletiek, Fenna H; Fitz, Hartmut; Bocanegra, Bruno R

2016-06-01

Rey et al. (2012) present data from a study with baboons that they interpret in support of the idea that center-embedded structures in human language have their origin in low level memory mechanisms and associative learning. Critically, the authors claim that the baboons showed a behavioral preference that is consistent with center-embedded sequences over other types of sequences. We argue that the baboons' response patterns suggest that two mechanisms are involved: first, they can be trained to associate a particular response with a particular stimulus, and, second, when faced with two conditioned stimuli in a row, they respond to the most recent one first, copying behavior they had been rewarded for during training. Although Rey et al. (2012) 'experiment shows that the baboons' behavior is driven by low level mechanisms, it is not clear how the animal behavior reported, bears on the phenomenon of Center Embedded structures in human syntax. Hence, (1) natural language syntax may indeed have been shaped by low level mechanisms, and (2) the baboons' behavior is driven by low level stimulus response learning, as Rey et al. propose. But is the second evidence for the first? We will discuss in what ways this study can and cannot give evidential value for explaining the origin of Center Embedded recursion in human grammar. More generally, their study provokes an interesting reflection on the use of animal studies in order to understand features of the human linguistic system. Copyright © 2015 Elsevier B.V. All rights reserved.

Cognitive Approach to Assessing Pragmatic Language Comprehension in Children with Specific Language Impairment

ERIC Educational Resources Information Center

Ryder, Nuala; Leinonen, Eeva; Schulz, Joerg

2008-01-01

Background: Pragmatic language impairment in children with specific language impairment has proved difficult to assess, and the nature of their abilities to comprehend pragmatic meaning has not been fully investigated. Aims: To develop both a cognitive approach to pragmatic language assessment based on Relevance Theory and an assessment tool for…

A Proposal of 3-dimensional Self-organizing Memory and Its Application to Knowledge Extraction from Natural Language

NASA Astrophysics Data System (ADS)

Sakakibara, Kai; Hagiwara, Masafumi

In this paper, we propose a 3-dimensional self-organizing memory and describe its application to knowledge extraction from natural language. First, the proposed system extracts a relation between words by JUMAN (morpheme analysis system) and KNP (syntax analysis system), and stores it in short-term memory. In the short-term memory, the relations are attenuated with the passage of processing. However, the relations with high frequency of appearance are stored in the long-term memory without attenuation. The relations in the long-term memory are placed to the proposed 3-dimensional self-organizing memory. We used a new learning algorithm called ``Potential Firing'' in the learning phase. In the recall phase, the proposed system recalls relational knowledge from the learned knowledge based on the input sentence. We used a new recall algorithm called ``Waterfall Recall'' in the recall phase. We added a function to respond to questions in natural language with ``yes/no'' in order to confirm the validity of proposed system by evaluating the quantity of correct answers.

A Diagrammatic Language for Biochemical Networks

NASA Astrophysics Data System (ADS)

Maimon, Ron

2002-03-01

I present a diagrammatic language for representing the structure of biochemical networks. The language is designed to represent modular structure in a computational fasion, with composition of reactions replacing functional composition. This notation is used to represent arbitrarily large networks efficiently. The notation finds its most natural use in representing biological interaction networks, but it is a general computing language appropriate to any naturally occuring computation. Unlike lambda-calculus, or text-derived languages, it does not impose a tree-structure on the diagrams, and so is more effective at representing biological fucntion than competing notations.

Factors Influencing Sensitivity to Lexical Tone in an Artificial Language: Implications for Second Language Learning

ERIC Educational Resources Information Center

Caldwell-Harris, Catherine L.; Lancaster, Alia; Ladd, D. Robert; Dediu, Dan; Christiansen, Morten H.

2015-01-01

This study examined whether musical training, ethnicity, and experience with a natural tone language influenced sensitivity to tone while listening to an artificial tone language. The language was designed with three tones, modeled after level-tone African languages. Participants listened to a 15-min random concatenation of six 3-syllable words.…

Storytelling, behavior planning, and language evolution in context.

PubMed

McBride, Glen

2014-01-01

An attempt is made to specify the structure of the hominin bands that began steps to language. Storytelling could evolve without need for language yet be strongly subject to natural selection and could provide a major feedback process in evolving language. A storytelling model is examined, including its effects on the evolution of consciousness and the possible timing of language evolution. Behavior planning is presented as a model of language evolution from storytelling. The behavior programming mechanism in both directions provide a model of creating and understanding behavior and language. Culture began with societies, then family evolution, family life in troops, but storytelling created a culture of experiences, a final step in the long process of achieving experienced adults by natural selection. Most language evolution occurred in conversations where evolving non-verbal feedback ensured mutual agreements on understanding. Natural language evolved in conversations with feedback providing understanding of changes.

Storytelling, behavior planning, and language evolution in context

PubMed Central

McBride, Glen

2014-01-01

An attempt is made to specify the structure of the hominin bands that began steps to language. Storytelling could evolve without need for language yet be strongly subject to natural selection and could provide a major feedback process in evolving language. A storytelling model is examined, including its effects on the evolution of consciousness and the possible timing of language evolution. Behavior planning is presented as a model of language evolution from storytelling. The behavior programming mechanism in both directions provide a model of creating and understanding behavior and language. Culture began with societies, then family evolution, family life in troops, but storytelling created a culture of experiences, a final step in the long process of achieving experienced adults by natural selection. Most language evolution occurred in conversations where evolving non-verbal feedback ensured mutual agreements on understanding. Natural language evolved in conversations with feedback providing understanding of changes. PMID:25360123

Multimedia CALLware: The Developer's Responsibility.

ERIC Educational Resources Information Center

Dodigovic, Marina

The early computer-assisted-language-learning (CALL) programs were silent and mostly limited to screen or printer supported written text as the prevailing communication resource. The advent of powerful graphics, sound and video combined with AI-based parsers and sound recognition devices gradually turned the computer into a rather anthropomorphic…

Extracting important information from Chinese Operation Notes with natural language processing methods.

PubMed

Wang, Hui; Zhang, Weide; Zeng, Qiang; Li, Zuofeng; Feng, Kaiyan; Liu, Lei

2014-04-01

Extracting information from unstructured clinical narratives is valuable for many clinical applications. Although natural Language Processing (NLP) methods have been profoundly studied in electronic medical records (EMR), few studies have explored NLP in extracting information from Chinese clinical narratives. In this study, we report the development and evaluation of extracting tumor-related information from operation notes of hepatic carcinomas which were written in Chinese. Using 86 operation notes manually annotated by physicians as the training set, we explored both rule-based and supervised machine-learning approaches. Evaluating on unseen 29 operation notes, our best approach yielded 69.6% in precision, 58.3% in recall and 63.5% F-score. Copyright © 2014 Elsevier Inc. All rights reserved.

American Sign Language

MedlinePlus

... Langue des Signes Française).Today’s ASL includes some elements of LSF plus the original local sign languages, which over the years ... evolves. It can also be used to model the essential elements and organization of natural language. Another NIDCD-funded research team is ...

Language, the Forgotten Content.

ERIC Educational Resources Information Center

Kelly, Patricia P., Ed.; Small, Robert C., Jr., Ed.

1987-01-01

The ways that students can learn about the nature of the English language and develop a sense of excitement about their language are explored in this focused journal issue. The titles of the essays and their authors are as follows: (1) "Language, the Forgotten Content" (R. Small and P. P. Kelly); (2) "What Should English Teachers…

Natural and Artificial Intelligence, Language, Consciousness, Emotion, and Anticipation

NASA Astrophysics Data System (ADS)

Dubois, Daniel M.

2010-11-01

The classical paradigm of the neural brain as the seat of human natural intelligence is too restrictive. This paper defends the idea that the neural ectoderm is the actual brain, based on the development of the human embryo. Indeed, the neural ectoderm includes the neural crest, given by pigment cells in the skin and ganglia of the autonomic nervous system, and the neural tube, given by the brain, the spinal cord, and motor neurons. So the brain is completely integrated in the ectoderm, and cannot work alone. The paper presents fundamental properties of the brain as follows. Firstly, Paul D. MacLean proposed the triune human brain, which consists to three brains in one, following the species evolution, given by the reptilian complex, the limbic system, and the neo-cortex. Secondly, the consciousness and conscious awareness are analysed. Thirdly, the anticipatory unconscious free will and conscious free veto are described in agreement with the experiments of Benjamin Libet. Fourthly, the main section explains the development of the human embryo and shows that the neural ectoderm is the whole neural brain. Fifthly, a conjecture is proposed that the neural brain is completely programmed with scripts written in biological low-level and high-level languages, in a manner similar to the programmed cells by the genetic code. Finally, it is concluded that the proposition of the neural ectoderm as the whole neural brain is a breakthrough in the understanding of the natural intelligence, and also in the future design of robots with artificial intelligence.

A Novel Model for Predicting Rehospitalization Risk Incorporating Physical Function, Cognitive Status, and Psychosocial Support Using Natural Language Processing.

PubMed

Greenwald, Jeffrey L; Cronin, Patrick R; Carballo, Victoria; Danaei, Goodarz; Choy, Garry

2017-03-01

With the increasing focus on reducing hospital readmissions in the United States, numerous readmissions risk prediction models have been proposed, mostly developed through analyses of structured data fields in electronic medical records and administrative databases. Three areas that may have an impact on readmission but are poorly captured using structured data sources are patients' physical function, cognitive status, and psychosocial environment and support. The objective of the study was to build a discriminative model using information germane to these 3 areas to identify hospitalized patients' risk for 30-day all cause readmissions. We conducted clinician focus groups to identify language used in the clinical record regarding these 3 areas. We then created a dataset including 30,000 inpatients, 10,000 from each of 3 hospitals, and searched those records for the focus group-derived language using natural language processing. A 30-day readmission prediction model was developed on 75% of the dataset and validated on the other 25% and also on hospital specific subsets. Focus group language was aggregated into 35 variables. The final model had 16 variables, a validated C-statistic of 0.74, and was well calibrated. Subset validation of the model by hospital yielded C-statistics of 0.70-0.75. Deriving a 30-day readmission risk prediction model through identification of physical, cognitive, and psychosocial issues using natural language processing yielded a model that performs similarly to the better performing models previously published with the added advantage of being based on clinically relevant factors and also automated and scalable. Because of the clinical relevance of the variables in the model, future research may be able to test if targeting interventions to identified risks results in reductions in readmissions.

Automating curation using a natural language processing pipeline

PubMed Central

Alex, Beatrice; Grover, Claire; Haddow, Barry; Kabadjov, Mijail; Klein, Ewan; Matthews, Michael; Tobin, Richard; Wang, Xinglong

2008-01-01

Background: The tasks in BioCreative II were designed to approximate some of the laborious work involved in curating biomedical research papers. The approach to these tasks taken by the University of Edinburgh team was to adapt and extend the existing natural language processing (NLP) system that we have developed as part of a commercial curation assistant. Although this paper concentrates on using NLP to assist with curation, the system can be equally employed to extract types of information from the literature that is immediately relevant to biologists in general. Results: Our system was among the highest performing on the interaction subtasks, and competitive performance on the gene mention task was achieved with minimal development effort. For the gene normalization task, a string matching technique that can be quickly applied to new domains was shown to perform close to average. Conclusion: The technologies being developed were shown to be readily adapted to the BioCreative II tasks. Although high performance may be obtained on individual tasks such as gene mention recognition and normalization, and document classification, tasks in which a number of components must be combined, such as detection and normalization of interacting protein pairs, are still challenging for NLP systems. PMID:18834488

Detecting the presence of an indwelling urinary catheter and urinary symptoms in hospitalized patients using natural language processing.

PubMed

Gundlapalli, Adi V; Divita, Guy; Redd, Andrew; Carter, Marjorie E; Ko, Danette; Rubin, Michael; Samore, Matthew; Strymish, Judith; Krein, Sarah; Gupta, Kalpana; Sales, Anne; Trautner, Barbara W

2017-07-01

To develop a natural language processing pipeline to extract positively asserted concepts related to the presence of an indwelling urinary catheter in hospitalized patients from the free text of the electronic medical note. The goal is to assist infection preventionists and other healthcare professionals in determining whether a patient has an indwelling urinary catheter when a catheter-associated urinary tract infection is suspected. Currently, data on indwelling urinary catheters is not consistently captured in the electronic medical record in structured format and thus cannot be reliably extracted for clinical and research purposes. We developed a lexicon of terms related to indwelling urinary catheters and urinary symptoms based on domain knowledge, prior experience in the field, and review of medical notes. A reference standard of 1595 randomly selected documents from inpatient admissions was annotated by human reviewers to identify all positively and negatively asserted concepts related to indwelling urinary catheters. We trained a natural language processing pipeline based on the V3NLP framework using 1050 documents and tested on 545 documents to determine agreement with the human reference standard. Metrics reported are positive predictive value and recall. The lexicon contained 590 terms related to the presence of an indwelling urinary catheter in various categories including insertion, care, change, and removal of urinary catheters and 67 terms for urinary symptoms. Nursing notes were the most frequent inpatient note titles in the reference standard document corpus; these also yielded the highest number of positively asserted concepts with respect to urinary catheters. Comparing the performance of the natural language processing pipeline against the human reference standard, the overall recall was 75% and positive predictive value was 99% on the training set; on the testing set, the recall was 72% and positive predictive value was 98%. The performance on

Using Language Learning Conditions in Mathematics. PEN 68.

ERIC Educational Resources Information Center

Stoessiger, Rex

This pamphlet reports on a project in Tasmania exploring whether the "natural learning conditions" approach to language learning could be adapted for mathematics. The connections between language and mathematics, as well as the natural learning processes of language learning are described in the pamphlet. The project itself is…

Positivity of the English Language

PubMed Central

Kloumann, Isabel M.; Danforth, Christopher M.; Harris, Kameron Decker; Bliss, Catherine A.; Dodds, Peter Sheridan

2012-01-01

Over the last million years, human language has emerged and evolved as a fundamental instrument of social communication and semiotic representation. People use language in part to convey emotional information, leading to the central and contingent questions: (1) What is the emotional spectrum of natural language? and (2) Are natural languages neutrally, positively, or negatively biased? Here, we report that the human-perceived positivity of over 10,000 of the most frequently used English words exhibits a clear positive bias. More deeply, we characterize and quantify distributions of word positivity for four large and distinct corpora, demonstrating that their form is broadly invariant with respect to frequency of word use. PMID:22247779

Attitudes and Language. Multilingual Matters: 83.

ERIC Educational Resources Information Center

Baker, Colin

This book examines language attitudes, focusing on individual attitudes toward majority and minority languages and bilingualism. Special emphasis is placed on research conducted on language attitudes in Wales toward the Welsh and English languages. Six chapters address the following: (1) the nature, definition, and measurement of language…

Language Program Evaluation

ERIC Educational Resources Information Center

Norris, John M.

2016-01-01

Language program evaluation is a pragmatic mode of inquiry that illuminates the complex nature of language-related interventions of various kinds, the factors that foster or constrain them, and the consequences that ensue. Program evaluation enables a variety of evidence-based decisions and actions, from designing programs and implementing…

Language and Social Identity Construction: A Study of a Russian Heritage Language Orthodox Christian School

ERIC Educational Resources Information Center

Moore, Ekaterina Leonidovna

2012-01-01

Grounded in discourse analytic and language socialization paradigms, this dissertation examines issues of language and social identity construction in children attending a Russian Heritage Language Orthodox Christian Saturday School in California. By conducting micro-analysis of naturally-occurring talk-in-interaction combined with longitudinal…

Crowdsourcing and curation: perspectives from biology and natural language processing

DOE PAGES

Hirschman, Lynette; Fort, Karën; Boué, Stéphanie; ...

2016-08-08

Crowdsourcing is increasingly utilized for performing tasks in both natural language processing and biocuration. Although there have been many applications of crowdsourcing in these fields, there have been fewer high-level discussions of the methodology and its applicability to biocuration. This paper explores crowdsourcing for biocuration through several case studies that highlight different ways of leveraging ‘the crowd’; these raise issues about the kind(s) of expertise needed, the motivations of participants, and questions related to feasibility, cost and quality. The paper is an outgrowth of a panel session held at BioCreative V (Seville, September 9–11, 2015). The session consisted of fourmore » short talks, followed by a discussion. In their talks, the panelists explored the role of expertise and the potential to improve crowd performance by training; the challenge of decomposing tasks to make them amenable to crowdsourcing; and the capture of biological data and metadata through community editing.« less

Crowdsourcing and curation: perspectives from biology and natural language processing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hirschman, Lynette; Fort, Karën; Boué, Stéphanie

Crowdsourcing is increasingly utilized for performing tasks in both natural language processing and biocuration. Although there have been many applications of crowdsourcing in these fields, there have been fewer high-level discussions of the methodology and its applicability to biocuration. This paper explores crowdsourcing for biocuration through several case studies that highlight different ways of leveraging ‘the crowd’; these raise issues about the kind(s) of expertise needed, the motivations of participants, and questions related to feasibility, cost and quality. The paper is an outgrowth of a panel session held at BioCreative V (Seville, September 9–11, 2015). The session consisted of fourmore » short talks, followed by a discussion. In their talks, the panelists explored the role of expertise and the potential to improve crowd performance by training; the challenge of decomposing tasks to make them amenable to crowdsourcing; and the capture of biological data and metadata through community editing.« less

Terminology model discovery using natural language processing and visualization techniques.

PubMed

Zhou, Li; Tao, Ying; Cimino, James J; Chen, Elizabeth S; Liu, Hongfang; Lussier, Yves A; Hripcsak, George; Friedman, Carol

2006-12-01

Medical terminologies are important for unambiguous encoding and exchange of clinical information. The traditional manual method of developing terminology models is time-consuming and limited in the number of phrases that a human developer can examine. In this paper, we present an automated method for developing medical terminology models based on natural language processing (NLP) and information visualization techniques. Surgical pathology reports were selected as the testing corpus for developing a pathology procedure terminology model. The use of a general NLP processor for the medical domain, MedLEE, provides an automated method for acquiring semantic structures from a free text corpus and sheds light on a new high-throughput method of medical terminology model development. The use of an information visualization technique supports the summarization and visualization of the large quantity of semantic structures generated from medical documents. We believe that a general method based on NLP and information visualization will facilitate the modeling of medical terminologies.

Generation of Natural-Language Textual Summaries from Longitudinal Clinical Records.

PubMed

Goldstein, Ayelet; Shahar, Yuval

2015-01-01

Physicians are required to interpret, abstract and present in free-text large amounts of clinical data in their daily tasks. This is especially true for chronic-disease domains, but holds also in other clinical domains. We have recently developed a prototype system, CliniText, which, given a time-oriented clinical database, and appropriate formal abstraction and summarization knowledge, combines the computational mechanisms of knowledge-based temporal data abstraction, textual summarization, abduction, and natural-language generation techniques, to generate an intelligent textual summary of longitudinal clinical data. We demonstrate our methodology, and the feasibility of providing a free-text summary of longitudinal electronic patient records, by generating summaries in two very different domains - Diabetes Management and Cardiothoracic surgery. In particular, we explain the process of generating a discharge summary of a patient who had undergone a Coronary Artery Bypass Graft operation, and a brief summary of the treatment of a diabetes patient for five years.

Language Sample Measures and Language Ability in Spanish English Bilingual Kindergarteners

PubMed Central

Bedore, Lisa M.; Peña, Elizabeth D.; Gillam, Ronald B.; Ho, Tsung-Han

2010-01-01

Measures of productivity and sentence organization are useful metrics for quantifying language development and language impairments in monolingual and bilingual children. It is not yet known what measures within and across languages are most informative when evaluating the language skills of bilingual children. The purpose of this study was to evaluate how measures of language productivity and organization in two languages converge with children’s measured language abilities on the Bilingual English Spanish Assessment (BESA), a standardized measure of language ability. 170 kindergarten age children who produced narrative language samples in Spanish and in English based on a wordless picture book were included in the analysis. Samples were analyzed for number of utterances, number of different words, mean length of utterance, and percentage of grammatical utterances. The best predictors of language ability as measured by the BESA scores were English MLU, English grammaticality, and Spanish grammaticality. Results are discussed in relationship to the nature of the measures in each of the languages and in regard to their potential utility for identifying low language ability in bilingual children. PMID:20955835

Conceptual Memory: A Theory and Computer Program for Processing the Meaning Content of Natural Language Utterances

DTIC Science & Technology

1974-07-01

iiWU -immmemmmmm This document was generated by the Stanford Artificial Intelligence Laboratory’s document compiler, "PUB" and reproducec’ on a...for more sophisticated artificial (programming) languages. The new issues became those of how to represent a grammar as precise syntactic structures...challenge lies in discovering - either by synthesis of an artificial system, or by analysis of a natural one - the underlying logical (a. opposed to

Does It Really Matter whether Students' Contributions Are Spoken versus Typed in an Intelligent Tutoring System with Natural Language?

ERIC Educational Resources Information Center

D'Mello, Sidney K.; Dowell, Nia; Graesser, Arthur

2011-01-01

There is the question of whether learning differs when students speak versus type their responses when interacting with intelligent tutoring systems with natural language dialogues. Theoretical bases exist for three contrasting hypotheses. The "speech facilitation" hypothesis predicts that spoken input will "increase" learning,…

Automatic reconstruction of a bacterial regulatory network using Natural Language Processing

PubMed Central

Rodríguez-Penagos, Carlos; Salgado, Heladia; Martínez-Flores, Irma; Collado-Vides, Julio

2007-01-01

Background Manual curation of biological databases, an expensive and labor-intensive process, is essential for high quality integrated data. In this paper we report the implementation of a state-of-the-art Natural Language Processing system that creates computer-readable networks of regulatory interactions directly from different collections of abstracts and full-text papers. Our major aim is to understand how automatic annotation using Text-Mining techniques can complement manual curation of biological databases. We implemented a rule-based system to generate networks from different sets of documents dealing with regulation in Escherichia coli K-12. Results Performance evaluation is based on the most comprehensive transcriptional regulation database for any organism, the manually-curated RegulonDB, 45% of which we were able to recreate automatically. From our automated analysis we were also able to find some new interactions from papers not already curated, or that were missed in the manual filtering and review of the literature. We also put forward a novel Regulatory Interaction Markup Language better suited than SBML for simultaneously representing data of interest for biologists and text miners. Conclusion Manual curation of the output of automatic processing of text is a good way to complement a more detailed review of the literature, either for validating the results of what has been already annotated, or for discovering facts and information that might have been overlooked at the triage or curation stages. PMID:17683642

Automatic Lung-RADS™ classification with a natural language processing system

PubMed Central

Beyer, Sebastian E.; Regis, Shawn M.; McKee, Andrea B.; Flacke, Sebastian; El Saadawi, Gilan; Wald, Christoph

2017-01-01

Background Our aim was to train a natural language processing (NLP) algorithm to capture imaging characteristics of lung nodules reported in a structured CT report and suggest the applicable Lung-RADS™ (LR) category. Methods Our study included structured, clinical reports of consecutive CT lung screening (CTLS) exams performed from 08/2014 to 08/2015 at an ACR accredited Lung Cancer Screening Center. All patients screened were at high-risk for lung cancer according to the NCCN Guidelines®. All exams were interpreted by one of three radiologists credentialed to read CTLS exams using LR using a standard reporting template. Training and test sets consisted of consecutive exams. Lung screening exams were divided into two groups: three training sets (500, 120, and 383 reports each) and one final evaluation set (498 reports). NLP algorithm results were compared with the gold standard of LR category assigned by the radiologist. Results The sensitivity/specificity of the NLP algorithm to correctly assign LR categories for suspicious nodules (LR 4) and positive nodules (LR 3/4) were 74.1%/98.6% and 75.0%/98.8% respectively. The majority of mismatches occurred in cases where pulmonary findings were present not currently addressed by LR. Misclassifications also resulted from the failure to identify exams as follow-up and the failure to completely characterize part-solid nodules. In a sub-group analysis among structured reports with standardized language, the sensitivity and specificity to detect LR 4 nodules were 87.0% and 99.5%, respectively. Conclusions An NLP system can accurately suggest the appropriate LR category from CTLS exam findings when standardized reporting is used. PMID:29221286

Automated encoding of clinical documents based on natural language processing.

PubMed

Friedman, Carol; Shagina, Lyudmila; Lussier, Yves; Hripcsak, George

2004-01-01

The aim of this study was to develop a method based on natural language processing (NLP) that automatically maps an entire clinical document to codes with modifiers and to quantitatively evaluate the method. An existing NLP system, MedLEE, was adapted to automatically generate codes. The method involves matching of structured output generated by MedLEE consisting of findings and modifiers to obtain the most specific code. Recall and precision applied to Unified Medical Language System (UMLS) coding were evaluated in two separate studies. Recall was measured using a test set of 150 randomly selected sentences, which were processed using MedLEE. Results were compared with a reference standard determined manually by seven experts. Precision was measured using a second test set of 150 randomly selected sentences from which UMLS codes were automatically generated by the method and then validated by experts. Recall of the system for UMLS coding of all terms was .77 (95% CI.72-.81), and for coding terms that had corresponding UMLS codes recall was .83 (.79-.87). Recall of the system for extracting all terms was .84 (.81-.88). Recall of the experts ranged from .69 to .91 for extracting terms. The precision of the system was .89 (.87-.91), and precision of the experts ranged from .61 to .91. Extraction of relevant clinical information and UMLS coding were accomplished using a method based on NLP. The method appeared to be comparable to or better than six experts. The advantage of the method is that it maps text to codes along with other related information, rendering the coded output suitable for effective retrieval.

Automated identification of patients with pulmonary nodules in an integrated health system using administrative health plan data, radiology reports, and natural language processing.

PubMed

Danforth, Kim N; Early, Megan I; Ngan, Sharon; Kosco, Anne E; Zheng, Chengyi; Gould, Michael K

2012-08-01

Lung nodules are commonly encountered in clinical practice, yet little is known about their management in community settings. An automated method for identifying patients with lung nodules would greatly facilitate research in this area. Using members of a large, community-based health plan from 2006 to 2010, we developed a method to identify patients with lung nodules, by combining five diagnostic codes, four procedural codes, and a natural language processing algorithm that performed free text searches of radiology transcripts. An experienced pulmonologist reviewed a random sample of 116 radiology transcripts, providing a reference standard for the natural language processing algorithm. With the use of an automated method, we identified 7112 unique members as having one or more incident lung nodules. The mean age of the patients was 65 years (standard deviation 14 years). There were slightly more women (54%) than men, and Hispanics and non-whites comprised 45% of the lung nodule cohort. Thirty-six percent were never smokers whereas 11% were current smokers. Fourteen percent of the patients were subsequently diagnosed with lung cancer. The sensitivity and specificity of the natural language processing algorithm for identifying the presence of lung nodules were 96% and 86%, respectively, compared with clinician review. Among the true positive transcripts in the validation sample, only 35% were solitary and unaccompanied by one or more associated findings, and 56% measured 8 to 30 mm in diameter. A combination of diagnostic codes, procedural codes, and a natural language processing algorithm for free text searching of radiology reports can accurately and efficiently identify patients with incident lung nodules, many of whom are subsequently diagnosed with lung cancer.

Wikipedia and Medicine: Quantifying Readership, Editors, and the Significance of Natural Language

PubMed Central

West, Andrew G

2015-01-01

Background Wikipedia is a collaboratively edited encyclopedia. One of the most popular websites on the Internet, it is known to be a frequently used source of health care information by both professionals and the lay public. Objective This paper quantifies the production and consumption of Wikipedia’s medical content along 4 dimensions. First, we measured the amount of medical content in both articles and bytes and, second, the citations that supported that content. Third, we analyzed the medical readership against that of other health care websites between Wikipedia’s natural language editions and its relationship with disease prevalence. Fourth, we surveyed the quantity/characteristics of Wikipedia’s medical contributors, including year-over-year participation trends and editor demographics. Methods Using a well-defined categorization infrastructure, we identified medically pertinent English-language Wikipedia articles and links to their foreign language equivalents. With these, Wikipedia can be queried to produce metadata and full texts for entire article histories. Wikipedia also makes available hourly reports that aggregate reader traffic at per-article granularity. An online survey was used to determine the background of contributors. Standard mining and visualization techniques (eg, aggregation queries, cumulative distribution functions, and/or correlation metrics) were applied to each of these datasets. Analysis focused on year-end 2013, but historical data permitted some longitudinal analysis. Results Wikipedia’s medical content (at the end of 2013) was made up of more than 155,000 articles and 1 billion bytes of text across more than 255 languages. This content was supported by more than 950,000 references. Content was viewed more than 4.88 billion times in 2013. This makes it one of if not the most viewed medical resource(s) globally. The core editor community numbered less than 300 and declined over the past 5 years. The members of this

A corpus of full-text journal articles is a robust evaluation tool for revealing differences in performance of biomedical natural language processing tools

PubMed Central

2012-01-01

Background We introduce the linguistic annotation of a corpus of 97 full-text biomedical publications, known as the Colorado Richly Annotated Full Text (CRAFT) corpus. We further assess the performance of existing tools for performing sentence splitting, tokenization, syntactic parsing, and named entity recognition on this corpus. Results Many biomedical natural language processing systems demonstrated large differences between their previously published results and their performance on the CRAFT corpus when tested with the publicly available models or rule sets. Trainable systems differed widely with respect to their ability to build high-performing models based on this data. Conclusions The finding that some systems were able to train high-performing models based on this corpus is additional evidence, beyond high inter-annotator agreement, that the quality of the CRAFT corpus is high. The overall poor performance of various systems indicates that considerable work needs to be done to enable natural language processing systems to work well when the input is full-text journal articles. The CRAFT corpus provides a valuable resource to the biomedical natural language processing community for evaluation and training of new models for biomedical full text publications. PMID:22901054

The Nature of the Language Faculty and Its Implications for Evolution of Language (Reply to Fitch, Hauser, and Chomsky)

ERIC Educational Resources Information Center

Jackendoff, Ray; Pinker, Steven

2005-01-01

In a continuation of the conversation with Fitch, Chomsky, and Hauser on the evolution of language, we examine their defense of the claim that the uniquely human, language-specific part of the language faculty (the ''narrow language faculty'') consists only of recursion, and that this part cannot be considered an adaptation to communication. We…

The Measurement of Language Diversity.

ERIC Educational Resources Information Center

Brougham, James

Accepting that language diversity is functionally related to other variables characterizing human societies, much discussion stems from the advantages or disadvantageous nature of language diversity in terms of national development and national unity. To discover ways of measuring language diversity would help, in part, to solve the language…

Automated identification of wound information in clinical notes of patients with heart diseases: Developing and validating a natural language processing application.

PubMed

Topaz, Maxim; Lai, Kenneth; Dowding, Dawn; Lei, Victor J; Zisberg, Anna; Bowles, Kathryn H; Zhou, Li

2016-12-01

Electronic health records are being increasingly used by nurses with up to 80% of the health data recorded as free text. However, only a few studies have developed nursing-relevant tools that help busy clinicians to identify information they need at the point of care. This study developed and validated one of the first automated natural language processing applications to extract wound information (wound type, pressure ulcer stage, wound size, anatomic location, and wound treatment) from free text clinical notes. First, two human annotators manually reviewed a purposeful training sample (n=360) and random test sample (n=1100) of clinical notes (including 50% discharge summaries and 50% outpatient notes), identified wound cases, and created a gold standard dataset. We then trained and tested our natural language processing system (known as MTERMS) to process the wound information. Finally, we assessed our automated approach by comparing system-generated findings against the gold standard. We also compared the prevalence of wound cases identified from free-text data with coded diagnoses in the structured data. The testing dataset included 101 notes (9.2%) with wound information. The overall system performance was good (F-measure is a compiled measure of system's accuracy=92.7%), with best results for wound treatment (F-measure=95.7%) and poorest results for wound size (F-measure=81.9%). Only 46.5% of wound notes had a structured code for a wound diagnosis. The natural language processing system achieved good performance on a subset of randomly selected discharge summaries and outpatient notes. In more than half of the wound notes, there were no coded wound diagnoses, which highlight the significance of using natural language processing to enrich clinical decision making. Our future steps will include expansion of the application's information coverage to other relevant wound factors and validation of the model with external data. Copyright © 2016 Elsevier Ltd. All

Using natural language processing to analyze physician modifications to data entry templates.

PubMed Central

Wilcox, Adam B.; Narus, Scott P.; Bowes, Watson A.

2002-01-01

Efficient data entry by clinicians remains a significant challenge for electronic medical records. Current approaches have largely focused on either structured data entry, which can be limiting in expressive power, or free-text entry, which restricts the use of the data for automated decision support. Text-based templates are a semi-structured data entry method that has been used to assist physicians in manually entering clinical notes, by allowing them to edit predefined example notes. We analyzed changes made to 18,726 sentences from text templates, using a natural language processor. The most common changes were addition or deletion of normal observations, or changes in certainty. We identified common modifications that could be captured in structured form by a graphical user interface. PMID:12463955

Dual Sticky Hierarchical Dirichlet Process Hidden Markov Model and Its Application to Natural Language Description of Motions.

PubMed

Hu, Weiming; Tian, Guodong; Kang, Yongxin; Yuan, Chunfeng; Maybank, Stephen

2017-09-25

In this paper, a new nonparametric Bayesian model called the dual sticky hierarchical Dirichlet process hidden Markov model (HDP-HMM) is proposed for mining activities from a collection of time series data such as trajectories. All the time series data are clustered. Each cluster of time series data, corresponding to a motion pattern, is modeled by an HMM. Our model postulates a set of HMMs that share a common set of states (topics in an analogy with topic models for document processing), but have unique transition distributions. For the application to motion trajectory modeling, topics correspond to motion activities. The learnt topics are clustered into atomic activities which are assigned predicates. We propose a Bayesian inference method to decompose a given trajectory into a sequence of atomic activities. On combining the learnt sources and sinks, semantic motion regions, and the learnt sequence of atomic activities, the action represented by the trajectory can be described in natural language in as automatic a way as possible. The effectiveness of our dual sticky HDP-HMM is validated on several trajectory datasets. The effectiveness of the natural language descriptions for motions is demonstrated on the vehicle trajectories extracted from a traffic scene.

A SUGGESTED BIBLIOGRAPHY FOR FOREIGN LANGUAGE TEACHERS.

ERIC Educational Resources Information Center

MICHEL, JOSEPH

DESIGNED FOR FOREIGN LANGUAGE TEACHERS AND PERSONS PREPARING TO BECOME FOREIGN LANGUAGE TEACHERS, THIS BIBLIOGRAPHY OF WORKS PUBLISHED BETWEEN 1892 AND 1966 CONTAINS SECTIONS OF--(1) THE NATURE AND FUNCTION OF LANGUAGE, (2) LINGUISTICS, INCLUDING APPLIED LINGUISTICS FOR SPECIFIC LANGUAGES, (3) PSYCHOLOGY OF LANGUAGE, (4) PHYSIOLOGY OF SPEECH, (5)…

Evaluation of Automated Natural Language Processing in the Further Development of Science Information Retrieval. String Program Reports No. 10.

ERIC Educational Resources Information Center

Sager, Naomi

This investigation matches the emerging techniques in computerized natural language processing against emerging needs for such techniques in the information field to evaluate and extend such techniques for future applications and to establish a basis and direction for further research toward these goals. An overview describes developments in the…

A Large-Scale Analysis of Variance in Written Language.

PubMed

Johns, Brendan T; Jamieson, Randall K

2018-01-22

The collection of very large text sources has revolutionized the study of natural language, leading to the development of several models of language learning and distributional semantics that extract sophisticated semantic representations of words based on the statistical redundancies contained within natural language (e.g., Griffiths, Steyvers, & Tenenbaum, ; Jones & Mewhort, ; Landauer & Dumais, ; Mikolov, Sutskever, Chen, Corrado, & Dean, ). The models treat knowledge as an interaction of processing mechanisms and the structure of language experience. But language experience is often treated agnostically. We report a distributional semantic analysis that shows written language in fiction books varies appreciably between books from the different genres, books from the same genre, and even books written by the same author. Given that current theories assume that word knowledge reflects an interaction between processing mechanisms and the language environment, the analysis shows the need for the field to engage in a more deliberate consideration and curation of the corpora used in computational studies of natural language processing. Copyright © 2018 Cognitive Science Society, Inc.

Knowledge acquisition from natural language for expert systems based on classification problem-solving methods

NASA Technical Reports Server (NTRS)

Gomez, Fernando

1989-01-01

It is shown how certain kinds of domain independent expert systems based on classification problem-solving methods can be constructed directly from natural language descriptions by a human expert. The expert knowledge is not translated into production rules. Rather, it is mapped into conceptual structures which are integrated into long-term memory (LTM). The resulting system is one in which problem-solving, retrieval and memory organization are integrated processes. In other words, the same algorithm and knowledge representation structures are shared by these processes. As a result of this, the system can answer questions, solve problems or reorganize LTM.

Recognition of a person named entity from the text written in a natural language

NASA Astrophysics Data System (ADS)

Dolbin, A. V.; Rozaliev, V. L.; Orlova, Y. A.

2017-01-01

This work is devoted to the semantic analysis of texts, which were written in a natural language. The main goal of the research was to compare latent Dirichlet allocation and latent semantic analysis to identify elements of the human appearance in the text. The completeness of information retrieval was chosen as the efficiency criteria for methods comparison. However, it was insufficient to choose only one method for achieving high recognition rates. Thus, additional methods were used for finding references to the personality in the text. All these methods are based on the created information model, which represents person’s appearance.

Voice-enabled Knowledge Engine using Flood Ontology and Natural Language Processing

NASA Astrophysics Data System (ADS)

Sermet, M. Y.; Demir, I.; Krajewski, W. F.

2015-12-01

The Iowa Flood Information System (IFIS) is a web-based platform developed by the Iowa Flood Center (IFC) to provide access to flood inundation maps, real-time flood conditions, flood forecasts, flood-related data, information and interactive visualizations for communities in Iowa. The IFIS is designed for use by general public, often people with no domain knowledge and limited general science background. To improve effective communication with such audience, we have introduced a voice-enabled knowledge engine on flood related issues in IFIS. Instead of navigating within many features and interfaces of the information system and web-based sources, the system provides dynamic computations based on a collection of built-in data, analysis, and methods. The IFIS Knowledge Engine connects to real-time stream gauges, in-house data sources, analysis and visualization tools to answer natural language questions. Our goal is the systematization of data and modeling results on flood related issues in Iowa, and to provide an interface for definitive answers to factual queries. The goal of the knowledge engine is to make all flood related knowledge in Iowa easily accessible to everyone, and support voice-enabled natural language input. We aim to integrate and curate all flood related data, implement analytical and visualization tools, and make it possible to compute answers from questions. The IFIS explicitly implements analytical methods and models, as algorithms, and curates all flood related data and resources so that all these resources are computable. The IFIS Knowledge Engine computes the answer by deriving it from its computational knowledge base. The knowledge engine processes the statement, access data warehouse, run complex database queries on the server-side and return outputs in various formats. This presentation provides an overview of IFIS Knowledge Engine, its unique information interface and functionality as an educational tool, and discusses the future plans

Teaching Additional Languages. Educational Practices Series 6.

ERIC Educational Resources Information Center

Judd, Elliot L.; Tan, Lihua; Walberg, Herbert J.

This booklet describes key principles of and research on teaching additional languages. The 10 chapters focus on the following: (1) "Comprehensible Input" (learners need exposure to meaningful, understandable language); (2) "Language Opportunities" (classroom activities should let students use natural and meaningful language with their…

A Large-Scale Analysis of Variance in Written Language

ERIC Educational Resources Information Center

Johns, Brendan T.; Jamieson, Randall K.

2018-01-01

The collection of very large text sources has revolutionized the study of natural language, leading to the development of several models of language learning and distributional semantics that extract sophisticated semantic representations of words based on the statistical redundancies contained within natural language (e.g., Griffiths, Steyvers,…

Language-Centered Social Studies: A Natural Integration.

ERIC Educational Resources Information Center

Barrera, Rosalinda B.; Aleman, Magdalena

1983-01-01

Described is a newspaper project in which elementary students report life as it was in the Middle Ages. Students are involved in a variety of language-centered activities. For example, they gather and evaluate information about medieval times and write, edit, and proofread articles for the newspaper. (RM)

An Examination of Natural Language as a Query Formation Tool for Retrieving Information on E-Health from Pub Med.

ERIC Educational Resources Information Center

Peterson, Gabriel M.; Su, Kuichun; Ries, James E.; Sievert, Mary Ellen C.

2002-01-01

Discussion of Internet use for information searches on health-related topics focuses on a study that examined complexity and variability of natural language in using search terms that express the concept of electronic health (e-health). Highlights include precision of retrieved information; shift in terminology; and queries using the Pub Med…

Integrating natural language processing and web GIS for interactive knowledge domain visualization

NASA Astrophysics Data System (ADS)

Du, Fangming

Recent years have seen a powerful shift towards data-rich environments throughout society. This has extended to a change in how the artifacts and products of scientific knowledge production can be analyzed and understood. Bottom-up approaches are on the rise that combine access to huge amounts of academic publications with advanced computer graphics and data processing tools, including natural language processing. Knowledge domain visualization is one of those multi-technology approaches, with its aim of turning domain-specific human knowledge into highly visual representations in order to better understand the structure and evolution of domain knowledge. For example, network visualizations built from co-author relations contained in academic publications can provide insight on how scholars collaborate with each other in one or multiple domains, and visualizations built from the text content of articles can help us understand the topical structure of knowledge domains. These knowledge domain visualizations need to support interactive viewing and exploration by users. Such spatialization efforts are increasingly looking to geography and GIS as a source of metaphors and practical technology solutions, even when non-georeferenced information is managed, analyzed, and visualized. When it comes to deploying spatialized representations online, web mapping and web GIS can provide practical technology solutions for interactive viewing of knowledge domain visualizations, from panning and zooming to the overlay of additional information. This thesis presents a novel combination of advanced natural language processing - in the form of topic modeling - with dimensionality reduction through self-organizing maps and the deployment of web mapping/GIS technology towards intuitive, GIS-like, exploration of a knowledge domain visualization. A complete workflow is proposed and implemented that processes any corpus of input text documents into a map form and leverages a web

Two Types of Definites in Natural Language

ERIC Educational Resources Information Center

Schwarz, Florian

2009-01-01

This thesis is concerned with the description and analysis of two semantically different types of definite articles in German. While the existence of distinct article paradigms in various Germanic dialects and other languages has been acknowledged in the descriptive literature for quite some time, the theoretical implications of their existence…

Some Implications of Research in Second Language Acquisition for Foreign Language Teaching.

ERIC Educational Resources Information Center

Lombardo, Linda

On the continuum along which theories of first and second language acquisition are located, the two extremes represent the classic controversy of nature (nativist) vs. nurture (environmentalist), while those in the middle view language acquisition as a result of a more or less balanced interaction between innate capacities and linguistic…

Surmounting the Tower of Babel: Monolingual and bilingual 2-year-olds' understanding of the nature of foreign language words.

PubMed

Byers-Heinlein, Krista; Chen, Ke Heng; Xu, Fei

2014-03-01

Languages function as independent and distinct conventional systems, and so each language uses different words to label the same objects. This study investigated whether 2-year-old children recognize that speakers of their native language and speakers of a foreign language do not share the same knowledge. Two groups of children unfamiliar with Mandarin were tested: monolingual English-learning children (n=24) and bilingual children learning English and another language (n=24). An English speaker taught children the novel label fep. On English mutual exclusivity trials, the speaker asked for the referent of a novel label (wug) in the presence of the fep and a novel object. Both monolingual and bilingual children disambiguated the reference of the novel word using a mutual exclusivity strategy, choosing the novel object rather than the fep. On similar trials with a Mandarin speaker, children were asked to find the referent of a novel Mandarin label kuò. Monolinguals again chose the novel object rather than the object with the English label fep, even though the Mandarin speaker had no access to conventional English words. Bilinguals did not respond systematically to the Mandarin speaker, suggesting that they had enhanced understanding of the Mandarin speaker's ignorance of English words. The results indicate that monolingual children initially expect words to be conventionally shared across all speakers-native and foreign. Early bilingual experience facilitates children's discovery of the nature of foreign language words. Copyright © 2013 Elsevier Inc. All rights reserved.

Disinventing and (Re)Constituting Languages

ERIC Educational Resources Information Center

Makoni, Sinfree; Pennycook, Alastair

2005-01-01

In this paper we argue that although the problematic nature of language construction has been acknowledged by a number of skeptical authors, including the recent claim in this journal (Reagan, 2004) that there is no such thing as English or any other language, this critical approach to language still needs to develop a broader understanding of the…

Language, Gesture, and Space.

ERIC Educational Resources Information Center

Emmorey, Karen, Ed.; Reilly, Judy S., Ed.

A collection of papers addresses a variety of issues regarding the nature and structure of sign language, gesture, and gesture systems. Articles include: "Theoretical Issues Relating Language, Gesture, and Space: An Overview" (Karen Emmorey, Judy S. Reilly); "Real, Surrogate, and Token Space: Grammatical Consequences in ASL American…

Naturalism and Ideological Work: How Is Family Language Policy Renegotiated as Both Parents and Children Learn a Threatened Minority Language?

ERIC Educational Resources Information Center

Armstrong, Timothy Currie

2014-01-01

Parents who enroll their children to be educated through a threatened minority language frequently do not speak that language themselves and classes in the language are sometimes offered to parents in the expectation that this will help them to support their children's education and to use the minority language in the home. Providing…

Facilitating cancer research using natural language processing of pathology reports.

PubMed

Xu, Hua; Anderson, Kristin; Grann, Victor R; Friedman, Carol

2004-01-01

Many ongoing clinical research projects, such as projects involving studies associated with cancer, involve manual capture of information in surgical pathology reports so that the information can be used to determine the eligibility of recruited patients for the study and to provide other information, such as cancer prognosis. Natural language processing (NLP) systems offer an alternative to automated coding, but pathology reports have certain features that are difficult for NLP systems. This paper describes how a preprocessor was integrated with an existing NLP system (MedLEE) in order to reduce modification to the NLP system and to improve performance. The work was done in conjunction with an ongoing clinical research project that assesses disparities and risks of developing breast cancer for minority women. An evaluation of the system was performed using manually coded data from the research project's database as a gold standard. The evaluation outcome showed that the extended NLP system had a sensitivity of 90.6% and a precision of 91.6%. Results indicated that this system performed satisfactorily for capturing information for the cancer research project.

Natural language processing and visualization in the molecular imaging domain.

PubMed

Tulipano, P Karina; Tao, Ying; Millar, William S; Zanzonico, Pat; Kolbert, Katherine; Xu, Hua; Yu, Hong; Chen, Lifeng; Lussier, Yves A; Friedman, Carol

2007-06-01

Molecular imaging is at the crossroads of genomic sciences and medical imaging. Information within the molecular imaging literature could be used to link to genomic and imaging information resources and to organize and index images in a way that is potentially useful to researchers. A number of natural language processing (NLP) systems are available to automatically extract information from genomic literature. One existing NLP system, known as BioMedLEE, automatically extracts biological information consisting of biomolecular substances and phenotypic data. This paper focuses on the adaptation, evaluation, and application of BioMedLEE to the molecular imaging domain. In order to adapt BioMedLEE for this domain, we extend an existing molecular imaging terminology and incorporate it into BioMedLEE. BioMedLEE's performance is assessed with a formal evaluation study. The system's performance, measured as recall and precision, is 0.74 (95% CI: [.70-.76]) and 0.70 (95% CI [.63-.76]), respectively. We adapt a JAVA viewer known as PGviewer for the simultaneous visualization of images with NLP extracted information.

Restrictions on biological adaptation in language evolution.

PubMed

Chater, Nick; Reali, Florencia; Christiansen, Morten H

2009-01-27

Language acquisition and processing are governed by genetic constraints. A crucial unresolved question is how far these genetic constraints have coevolved with language, perhaps resulting in a highly specialized and species-specific language "module," and how much language acquisition and processing redeploy preexisting cognitive machinery. In the present work, we explored the circumstances under which genes encoding language-specific properties could have coevolved with language itself. We present a theoretical model, implemented in computer simulations, of key aspects of the interaction of genes and language. Our results show that genes for language could have coevolved only with highly stable aspects of the linguistic environment; a rapidly changing linguistic environment does not provide a stable target for natural selection. Thus, a biological endowment could not coevolve with properties of language that began as learned cultural conventions, because cultural conventions change much more rapidly than genes. We argue that this rules out the possibility that arbitrary properties of language, including abstract syntactic principles governing phrase structure, case marking, and agreement, have been built into a "language module" by natural selection. The genetic basis of human language acquisition and processing did not coevolve with language, but primarily predates the emergence of language. As suggested by Darwin, the fit between language and its underlying mechanisms arose because language has evolved to fit the human brain, rather than the reverse.

Understanding Student Language: An Unsupervised Dialogue Act Classification Approach

ERIC Educational Resources Information Center

Ezen-Can, Aysu; Boyer, Kristy Elizabeth

2015-01-01

Within the landscape of educational data, textual natural language is an increasingly vast source of learning-centered interactions. In natural language dialogue, student contributions hold important information about knowledge and goals. Automatically modeling the dialogue act of these student utterances is crucial for scaling natural language…

Bilingual Language Switching in the Laboratory versus in the Wild: The Spatiotemporal Dynamics of Adaptive Language Control

PubMed Central

2017-01-01

For a bilingual human, every utterance requires a choice about which language to use. This choice is commonly regarded as part of general executive control, engaging prefrontal and anterior cingulate cortices similarly to many types of effortful task switching. However, although language control within artificial switching paradigms has been heavily studied, the neurobiology of natural switching within socially cued situations has not been characterized. Additionally, although theoretical models address how language control mechanisms adapt to the distinct demands of different interactional contexts, these predictions have not been empirically tested. We used MEG (RRID: NIFINV:nlx_inv_090918) to investigate language switching in multiple contexts ranging from completely artificial to the comprehension of a fully natural bilingual conversation recorded “in the wild.” Our results showed less anterior cingulate and prefrontal cortex involvement for more natural switching. In production, voluntary switching did not engage the prefrontal cortex or elicit behavioral switch costs. In comprehension, while laboratory switches recruited executive control areas, fully natural switching within a conversation only engaged auditory cortices. Multivariate pattern analyses revealed that, in production, interlocutor identity was represented in a sustained fashion throughout the different stages of language planning until speech onset. In comprehension, however, a biphasic pattern was observed: interlocutor identity was first represented at the presentation of the interlocutor and then again at the presentation of the auditory word. In all, our findings underscore the importance of ecologically valid experimental paradigms and offer the first neurophysiological characterization of language control in a range of situations simulating real life to various degrees. SIGNIFICANCE STATEMENT Bilingualism is an inherently social phenomenon, interactional context fully determining

Validation of the "Chinese Language Classroom Learning Environment Inventory" for Investigating the Nature of Chinese Language Classrooms

ERIC Educational Resources Information Center

Lian, Chua Siew; Wong, Angela F. L.; Der-Thanq, Victor Chen

2006-01-01

The Chinese Language Classroom Environment Inventory (CLCEI) is a bilingual instrument developed for use in measuring students' and teachers' perceptions toward their Chinese Language classroom learning environments in Singapore secondary schools. The English version of the CLCEI was customised from the English version of the "What is…

Saying What You're Looking For: Linguistics Meets Video Search.

PubMed

Barrett, Daniel Paul; Barbu, Andrei; Siddharth, N; Siskind, Jeffrey Mark

2016-10-01

We present an approach to searching large video corpora for clips which depict a natural-language query in the form of a sentence. Compositional semantics is used to encode subtle meaning differences lost in other approaches, such as the difference between two sentences which have identical words but entirely different meaning: The person rode the horse versus The horse rode the person. Given a sentential query and a natural-language parser, we produce a score indicating how well a video clip depicts that sentence for each clip in a corpus and return a ranked list of clips. Two fundamental problems are addressed simultaneously: detecting and tracking objects, and recognizing whether those tracks depict the query. Because both tracking and object detection are unreliable, our approach uses the sentential query to focus the tracker on the relevant participants and ensures that the resulting tracks are described by the sentential query. While most earlier work was limited to single-word queries which correspond to either verbs or nouns, we search for complex queries which contain multiple phrases, such as prepositional phrases, and modifiers, such as adverbs. We demonstrate this approach by searching for 2,627 naturally elicited sentential queries in 10 Hollywood movies.

Treating conduct disorder: An effectiveness and natural language analysis study of a new family-centred intervention program.

PubMed

Stevens, Kimberly A; Ronan, Prof Kevin; Davies, Gene

2017-05-01

This paper reports on a new family-centred, feedback-informed intervention focused on evaluating therapeutic outcomes and language changes across treatment for conduct disorder (CD). The study included 26 youth and families from a larger randomised, controlled trial (Ronan et al., in preparation). Outcome measures reflected family functioning/youth compliance, delinquency, and family goal attainment. First- and last-treatment session audio files were transcribed into more than 286,000 words and evaluated through the Linguistic Inquiry and Word Count Analysis program (Pennebaker et al., 2007). Significant outcomes across family functioning/youth compliance, delinquency, goal attainment and word usage reflected moderate-strong effect sizes. Benchmarking findings also revealed reduced time of treatment delivery compared to a gold standard approach. Linguistic analysis revealed specific language changes across treatment. For caregivers, increased first person, action-oriented, present tense, and assent type words and decreased sadness words were found; for youth, significant reduction in use of leisure words. This study is the first using lexical analyses of natural language to assess change across treatment for conduct disordered youth and families. Such findings provided strong support for program tenets; others, more speculative support. Copyright © 2016. Published by Elsevier B.V.

Mayo clinical Text Analysis and Knowledge Extraction System (cTAKES): architecture, component evaluation and applications

PubMed Central

Masanz, James J; Ogren, Philip V; Zheng, Jiaping; Sohn, Sunghwan; Kipper-Schuler, Karin C; Chute, Christopher G

2010-01-01

We aim to build and evaluate an open-source natural language processing system for information extraction from electronic medical record clinical free-text. We describe and evaluate our system, the clinical Text Analysis and Knowledge Extraction System (cTAKES), released open-source at http://www.ohnlp.org. The cTAKES builds on existing open-source technologies—the Unstructured Information Management Architecture framework and OpenNLP natural language processing toolkit. Its components, specifically trained for the clinical domain, create rich linguistic and semantic annotations. Performance of individual components: sentence boundary detector accuracy=0.949; tokenizer accuracy=0.949; part-of-speech tagger accuracy=0.936; shallow parser F-score=0.924; named entity recognizer and system-level evaluation F-score=0.715 for exact and 0.824 for overlapping spans, and accuracy for concept mapping, negation, and status attributes for exact and overlapping spans of 0.957, 0.943, 0.859, and 0.580, 0.939, and 0.839, respectively. Overall performance is discussed against five applications. The cTAKES annotations are the foundation for methods and modules for higher-level semantic processing of clinical free-text. PMID:20819853

A natural language-based presentation of cognitive stimulation to people with dementia in assistive technology: A pilot study.

PubMed

Dethlefs, Nina; Milders, Maarten; Cuayáhuitl, Heriberto; Al-Salkini, Turkey; Douglas, Lorraine

2017-12-01

Currently, an estimated 36 million people worldwide are affected by Alzheimer's disease or related dementias. In the absence of a cure, non-pharmacological interventions, such as cognitive stimulation, which slow down the rate of deterioration can benefit people with dementia and their caregivers. Such interventions have shown to improve well-being and slow down the rate of cognitive decline. It has further been shown that cognitive stimulation in interaction with a computer is as effective as with a human. However, the need to operate a computer often represents a difficulty for the elderly and stands in the way of widespread adoption. A possible solution to this obstacle is to provide a spoken natural language interface that allows people with dementia to interact with the cognitive stimulation software in the same way as they would interact with a human caregiver. This makes the assistive technology accessible to users regardless of their technical skills and provides a fully intuitive user experience. This article describes a pilot study that evaluated the feasibility of computer-based cognitive stimulation through a spoken natural language interface. Prototype software was evaluated with 23 users, including healthy elderly people and people with dementia. Feedback was overwhelmingly positive.

An Evolving Ecosystem for Natural Language Processing in Department of Veterans Affairs.

PubMed

Garvin, Jennifer H; Kalsy, Megha; Brandt, Cynthia; Luther, Stephen L; Divita, Guy; Coronado, Gregory; Redd, Doug; Christensen, Carrie; Hill, Brent; Kelly, Natalie; Treitler, Qing Zeng

2017-02-01

In an ideal clinical Natural Language Processing (NLP) ecosystem, researchers and developers would be able to collaborate with others, undertake validation of NLP systems, components, and related resources, and disseminate them. We captured requirements and formative evaluation data from the Veterans Affairs (VA) Clinical NLP Ecosystem stakeholders using semi-structured interviews and meeting discussions. We developed a coding rubric to code interviews. We assessed inter-coder reliability using percent agreement and the kappa statistic. We undertook 15 interviews and held two workshop discussions. The main areas of requirements related to; design and functionality, resources, and information. Stakeholders also confirmed the vision of the second generation of the Ecosystem and recommendations included; adding mechanisms to better understand terms, measuring collaboration to demonstrate value, and datasets/tools to navigate spelling errors with consumer language, among others. Stakeholders also recommended capability to: communicate with developers working on the next version of the VA electronic health record (VistA Evolution), provide a mechanism to automatically monitor download of tools and to automatically provide a summary of the downloads to Ecosystem contributors and funders. After three rounds of coding and discussion, we determined the percent agreement of two coders to be 97.2% and the kappa to be 0.7851. The vision of the VA Clinical NLP Ecosystem met stakeholder needs. Interviews and discussion provided key requirements that inform the design of the VA Clinical NLP Ecosystem.

Natural Language Processing in aid of FlyBase curators

PubMed Central

Karamanis, Nikiforos; Seal, Ruth; Lewin, Ian; McQuilton, Peter; Vlachos, Andreas; Gasperin, Caroline; Drysdale, Rachel; Briscoe, Ted

2008-01-01

Background Despite increasing interest in applying Natural Language Processing (NLP) to biomedical text, whether this technology can facilitate tasks such as database curation remains unclear. Results PaperBrowser is the first NLP-powered interface that was developed under a user-centered approach to improve the way in which FlyBase curators navigate an article. In this paper, we first discuss how observing curators at work informed the design and evaluation of PaperBrowser. Then, we present how we appraise PaperBrowser's navigational functionalities in a user-based study using a text highlighting task and evaluation criteria of Human-Computer Interaction. Our results show that PaperBrowser reduces the amount of interactions between two highlighting events and therefore improves navigational efficiency by about 58% compared to the navigational mechanism that was previously available to the curators. Moreover, PaperBrowser is shown to provide curators with enhanced navigational utility by over 74% irrespective of the different ways in which they highlight text in the article. Conclusion We show that state-of-the-art performance in certain NLP tasks such as Named Entity Recognition and Anaphora Resolution can be combined with the navigational functionalities of PaperBrowser to support curation quite successfully. PMID:18410678

A common type system for clinical natural language processing.

PubMed

Wu, Stephen T; Kaggal, Vinod C; Dligach, Dmitriy; Masanz, James J; Chen, Pei; Becker, Lee; Chapman, Wendy W; Savova, Guergana K; Liu, Hongfang; Chute, Christopher G

2013-01-03

One challenge in reusing clinical data stored in electronic medical records is that these data are heterogenous. Clinical Natural Language Processing (NLP) plays an important role in transforming information in clinical text to a standard representation that is comparable and interoperable. Information may be processed and shared when a type system specifies the allowable data structures. Therefore, we aim to define a common type system for clinical NLP that enables interoperability between structured and unstructured data generated in different clinical settings. We describe a common type system for clinical NLP that has an end target of deep semantics based on Clinical Element Models (CEMs), thus interoperating with structured data and accommodating diverse NLP approaches. The type system has been implemented in UIMA (Unstructured Information Management Architecture) and is fully functional in a popular open-source clinical NLP system, cTAKES (clinical Text Analysis and Knowledge Extraction System) versions 2.0 and later. We have created a type system that targets deep semantics, thereby allowing for NLP systems to encapsulate knowledge from text and share it alongside heterogenous clinical data sources. Rather than surface semantics that are typically the end product of NLP algorithms, CEM-based semantics explicitly build in deep clinical semantics as the point of interoperability with more structured data types.

Of Substance: The Nature of Language Effects on Entity Construal

ERIC Educational Resources Information Center

Li, Peggy; Dunham, Yarrow; Carey, Susan

2009-01-01

Shown an entity (e.g., a plastic whisk) labeled by a novel noun in neutral syntax, speakers of Japanese, a classifier language, are more likely to assume the noun refers to the substance (plastic) than are speakers of English, a count/mass language, who are instead more likely to assume it refers to the object kind [whisk; Imai, M., & Gentner, D.…

A New Essential Functions Installed DWH in Hospital Information System: Process Mining Techniques and Natural Language Processing.

PubMed

Honda, Masayuki; Matsumoto, Takehiro

2017-01-01

Several kinds of event log data produced in daily clinical activities have yet to be used for secure and efficient improvement of hospital activities. Data Warehouse systems in Hospital Information Systems used for the analysis of structured data such as disease, lab-tests, and medications, have also shown efficient outcomes. This article is focused on two kinds of essential functions: process mining using log data and non-structured data analysis via Natural Language Processing.

Language learning, language use and the evolution of linguistic variation

PubMed Central

Perfors, Amy; Fehér, Olga; Samara, Anna; Swoboda, Kate; Wonnacott, Elizabeth

2017-01-01

Linguistic universals arise from the interaction between the processes of language learning and language use. A test case for the relationship between these factors is linguistic variation, which tends to be conditioned on linguistic or sociolinguistic criteria. How can we explain the scarcity of unpredictable variation in natural language, and to what extent is this property of language a straightforward reflection of biases in statistical learning? We review three strands of experimental work exploring these questions, and introduce a Bayesian model of the learning and transmission of linguistic variation along with a closely matched artificial language learning experiment with adult participants. Our results show that while the biases of language learners can potentially play a role in shaping linguistic systems, the relationship between biases of learners and the structure of languages is not straightforward. Weak biases can have strong effects on language structure as they accumulate over repeated transmission. But the opposite can also be true: strong biases can have weak or no effects. Furthermore, the use of language during interaction can reshape linguistic systems. Combining data and insights from studies of learning, transmission and use is therefore essential if we are to understand how biases in statistical learning interact with language transmission and language use to shape the structural properties of language. This article is part of the themed issue ‘New frontiers for statistical learning in the cognitive sciences’. PMID:27872370