An Integrated Robust Parsing using Multiple Knowledge Sources

Natural language communication with computers has been a major goal of arti cial intelligence (AI). Database systems and expert systems require a exible interface that allows users to communicate through natural language such as Japanese and English, if users are not able to communicate with the systems in arti cial command languages. In order to satisfy this requirement, many natural language processing (NLP) systems have been proposed, but most of them assume that all input sentences from users are grammatically correct. However, when users communicate with the NLP system, they may put grammatically ill-formed sentences, especially in spoken language interfaces. For example, users often omit some words, change word order, or make some careless errors such as agreement errors, spelling errors, and adding of extra words. To use NLP systems in practical applications, we need to construct an NLP system having a capability of handling not only grammatically well-formed sentences but also grammatically ill-formed ones. Along that line, many studies have been made on processing grammatically ill-formed sentences, but most of them have used either syntactic or semantic information and dealt with particular types of ill-formedness. In order to process grammatically ill-formed sentences exibly, it is necessary to utilize syntactic, semantic, and contextual information in an integrated manner. These types of information belong to linguistic information. In recent years, large corpora and Doctor's Thesis, Department of Information Processing, Graduate School of Information Science, Nara Institute of Science and Technology, NAIST-IS-DT9561005, February 9, 1998.

[1]  John D. Lafferty,et al.  Towards History-based Grammars: Using Richer Models for Probabilistic Parsing , 1993, ACL.

[2]  Hozumi Tanaka,et al.  A Parallel Chart-Based Parser for Analyzing Ill-Formed Inputs , 1995 .

[3]  Glenn Carroll,et al.  Context-Sensitive Statistics For Improved Grammatical Language Models , 1994, AAAI.

[4]  Osamu Imaichi.  An Integrated Framework for Processing Grammatically Ill-Formed Sentences , 1995 .

[5]  Norman K. Sondheimer,et al.  Meta-Rules as a Basis for Processing III-Formed Input , 1983, Am. J. Comput. Linguistics.

[6]  Geoffrey K. Pullum,et al.  Generalized Phrase Structure Grammar , 1985 .

[7]  Yuji Matsumoto,et al.  Current Issues in Robust Natural Language Processing , 1994 .

[8]  Jungyun Seo,et al.  A Robust Parser Based on Syntactic Information , 1995, EACL.

[9]  Douglas E. Appelt,et al.  Robust Processing of Real-World Natural-Language Texts , 1992, ANLP.

[10]  Giorgio Satta,et al.  Bidirectional Context-Free Grammar Parsing for Natural Language Processing , 1994, Artif. Intell..

[11]  James F. Allen,et al.  Tagging Speech Repairs , 1994, HLT.

[12]  Norman K. Sondheimer,et al.  Relaxation Techniques for Parsing Grammatically III-Formed Input in Natural Language Understanding Systems , 1981, Am. J. Comput. Linguistics.

[13]  Mitchell P. Marcus,et al.  A theory of syntactic recognition for natural language , 1979 .

[14]  C. M. Eastman,et al.  On the Need for Parsing Ill-Formed Input , 1981, CL.

[15]  Noboru Ohnishi,et al.  A Parser Coping With Self-Repaired Japanese Utterances And Large Corpus-Based Evaluation , 1994, COLING.

[16]  Fernando Pereira,et al.  Inside-Outside Reestimation From Partially Bracketed Corpora , 1992, HLT.

[17]  Alfred V. Aho,et al.  The Theory of Parsing, Translation, and Compiling , 1972 .

[18]  Jerry R. Hobbs,et al.  Interpretation as Abduction , 1993, Artif. Intell..

[19]  Yuji Matsumoto,et al.  Japanese Morphological Analysis System ChaSen version 2.0 Manual , 1999 .

[20]  Philip J. Hayes,et al.  Flexible Parsing , 1980, ACL.

[21]  Jordan B. Pollack,et al.  Massively Parallel Parsing: A Strongly Interactive Model of Natural Language Interpretation , 1988, Cogn. Sci..

[22]  Yorick Wilks,et al.  A Preferential, Pattern-Seeking, Semantics for Natural Language Inference , 1975, Artif. Intell..

[23]  郡司 隆男.  Japanese phrase structure grammar : a unification-based approach , 1987 .

[24]  David D. McDonald.  An Efficient Chart-based Algorithm for Partial-Parsing of Unrestricted Texts , 1992, ANLP.

[25]  James F. Allen,et al.  Deyecting and Correcting Speech Repairs , 1994, ACL.

[26]  Tetsuya Nasukawa.  Robust Parsing Based on Discourse Information: Completing Partial Parses of Ill-Formed Sentences on the Basis of Discourse Information , 1995, ACL.

[27]  Masaru Tomita,et al.  Parsing noisy sentences , 1988, COLING.

[28]  Scott Weinstein,et al.  Centering: A Framework for Modeling the Local Coherence of Discourse , 1995, CL.

[29]  Ralph M. Weischedel,et al.  Responding Intelligently to Unparsable Inputs , 1980, Am. J. Comput. Linguistics.

[30]  Tadashi Nomoto,et al.  Resolving Zero Anaphora in Japanese , 1993, EACL.

[31]  Yorick Wilks,et al.  Preference Semantics, III-Formedness, and Metaphor , 1983, Am. J. Comput. Linguistics.

[32]  Jaime G. Carbonell,et al.  Recovery Strategies for Parsing Extragrammatical Language , 1983, CL.

[33]  Ivan A. Sag,et al.  Book Reviews: Head-driven Phrase Structure Grammar and German in Head-driven Phrase-structure Grammar , 1996, CL.

[34]  Victor Poznański.  A relevance-based utterance processing system , 1992 .

[35]  Eugene Charniak,et al.  Figures of Merit for Best-First Probabilistic Chart Parsing , 1998, Comput. Linguistics.

[36]  Ted Briscoe,et al.  Robust stochastic parsing using the inside-outside algorithm , 1994, ArXiv.

[37]  Martin Kay,et al.  Algorithm schemata and data structures in syntactic processing , 1986 .

[38]  Bob Carpenter,et al.  The logic of typed feature structures , 1992 .

[39]  Chris Mellish,et al.  Some Chart-Based Techniques for Parsing Ill-Formed Input , 1989, ACL.

[40]  Ralph Grishman,et al.  A Procedure for Quantitatively Comparing the Syntactic Coverage of English Grammars , 1991, HLT.

[41]  Klaas Sikkel,et al.  Parsing Schemata , 1997, Texts in Theoretical Computer Science An EATCS Series.

[42]  Scott Miller,et al.  Automatic Grammar Acquisition , 1994, HLT.

[43]  Jin Wang.  Syntactic Preferences For Robust Parsing With Semantic Preferences , 1992, COLING.

[44]  David M. Magerman.  Statistical Decision-Tree Models for Parsing , 1995, ACL.

[45]  William A. Woods,et al.  Computational Linguistics Transition Network Grammars for Natural Language Analysis , 2022 .

[46]  Jaime G. Carbonell,et al.  Robust Parsing Using Multiple Construction-Specific Strategies , 1987 .

[47]  Jay Earley,et al.  An efficient context-free parsing algorithm , 1970, Commun. ACM.

[48]  Graeme Hirst,et al.  Semantic Interpretation and the Resolution of Ambiguity , 1987, Studies in natural language processing.

[49]  Robert Dale,et al.  Towards Robust PATR , 1992, COLING.

[50]  Michael Collins,et al.  A New Statistical Parser Based on Bigram Lexical Dependencies , 1996, ACL.

[51]  M. F.,et al.  Bibliography , 1985, Experimental Gerontology.

[52]  John Bear,et al.  Integrating Multiple Knowledge Sources for Detection and Correction of Repairs in Human-Computer Dialog , 1992, ACL.

[53]  David E. Johnson,et al.  Arc Pair Grammar , 1980 .

[54]  Eugene Charniak,et al.  Passing Markers: A Theory of Contextual Influence in Language Comprehension , 1983, Cogn. Sci..

[55]  David Stallard,et al.  The Semantic Linker- A New Fragment Combining Method , 1993, HLT.

[56]  Tsuneaki Kato,et al.  Yet Another Chart-Based Technique for Parsing Ill-Formed Input , 1994, ANLP.

[57]  Yuji Matsumoto,et al.  An Integrated Parsing Method using Stochastic Information and Grammatical Con-straints , 1998 .

[58]  Steven L. Lytinen,et al.  ULINK: A Semantics-Driven Approach to Understanding Ungrammatical Input , 1991, AAAI.

[59]  Stuart M. Shieber,et al.  An Introduction to Unification-Based Approaches to Grammar , 1986, CSLI Lecture Notes.

[60]  Glenn Carroll,et al.  Two Experiments on Learning Probabilistic Dependency Grammars from Corpora , 1992 .

[61]  Michael Collins,et al.  Three Generative, Lexicalised Models for Statistical Parsing , 1997, ACL.

[62]  Yuji Matsumoto,et al.  Integration of Syntactic, Semantic and Contextual Information in Processing Grammatically Ill-Formed Inputs , 1995, IJCAI.

[63]  Donald Hindle,et al.  Deterministic Parsing of Syntactic Non-fluencies , 1983, ACL.

[64]  Eugene Charniak,et al.  Statistical Parsing with a Context-Free Grammar and Word Statistics , 1997, AAAI/IAAI.

[65]  Ivan A. Sag,et al.  Information-Based Syntax and Semantics: Volume 1, Fundamentals , 1987 .

[66]  Ellen Riloff,et al.  Connectionist, Statistical and Symbolic Approaches to Learning for Natural Language Processing , 1996, Lecture Notes in Computer Science.

[67]  Lance A. Miller,et al.  Parse Fitting and Prose Fixing: Getting a Hold on III-Formedness , 1983, Am. J. Comput. Linguistics.

[68]  Yuji Matsumoto,et al.  An Efficient Parsing Method using Dependency Information and its Application to Robust Parsing , 1997 .

[69]  Eugene Charniak,et al.  Statistical language learning , 1997 .

[70]  Keith Devlin,et al.  Logic and information , 1991 .

[71]  Julia Hirschberg,et al.  A Speech-First Model for Repair Detection and Correction , 1993, HLT.

[72]  Yuji Matsumoto,et al.  Training stochastic grammars on semantical categories , 1995, Learning for Natural Language Processing.

[73]  Karen Jensen,et al.  The Fitted Parse: 100% Parsing Capability in a Syntactic Grammar of English , 1983, ANLP.