Knowledge-Based Systems for Natural Language Processing

This article reviews some of the underlying principles and methodological issues in developing knowledge-based methods for natural language processing. Some of the best practices in knowledgebased NLP will be illustrated through several NLP systems that use semantic and world knowledge to resolve ambiguities and extract meanings of sentences. Issues in knowledge acquisition and representation for NLP will also be addressed. The article includes pointers to books, journals, conferences, and electronic archives for further information. A revised version of this article will appear as a chapter in the Handbook for Computer Science and Engineering to be published by CRC Press in Fall 1996.

[1]  Ashok K. Goel,et al.  Situating natural language understanding within experience-based design , 1994, Int. J. Hum. Comput. Stud..

[2]  M. R. Genesereth,et al.  Knowledge Interchange Format Version 3.0 Reference Manual , 1992, LICS 1992.

[3]  Daniel Jurafsky,et al.  An On-Line Computational Model of Human Sentence Interpretation , 1992, AAAI.

[4]  Charles Eugene Martin,et al.  Direct memory access parsing , 1992 .

[5]  Sergei Nirenburg,et al.  A Situated Ontology for Practical NLP , 1995 .

[6]  Sergei Nirenburg,et al.  An MAT Tool and Its Effectiveness , 1993, HLT.

[7]  Carol Peters,et al.  A Translator's Workstation , 1992, COLING.

[8]  Sergei Nirenburg,et al.  Meaning Representation For Knowledge Sharing In Practical Machine Translation , 1996 .

[9]  Janet D. Fodor,et al.  The sausage machine: A new two-stage parsing model , 1978, Cognition.

[10]  Allen Newell,et al.  SOAR: An Architecture for General Intelligence , 1987, Artif. Intell..

[11]  Kavi Mahesh,et al.  Syntax-semantics interaction in sentence understanding , 1995 .

[12]  Sergei Nirenburg,et al.  Semantic Classification for Practical Natural Language Processing , 1995 .

[13]  Avron Barr.  Natural Language Understanding , 1980, AI Mag..

[14]  R. Schank,et al.  Inside Computer Understanding: Five Programs Plus Miniatures , 1982 .

[15]  Kevin Knight,et al.  Building a Large-Scale Knowledge Base for Machine Translation , 1994, AAAI.

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

[17]  Pierrette Bouillon,et al.  Semantic Lexicons: The Cornerstone for Lexical Choice in Natural Language Generation , 1994, INLG.

[18]  Chuck Rieger,et al.  Parsing and comprehending with word experts (a theory and its realization) , 1982 .

[19]  Peter Norvig,et al.  Artificial Intelligence: A Modern Approach , 1995 .

[20]  Sergei Nirenburg,et al.  Book Reviews: Machine Translation: A Knowledge-Based Approach , 1993, CL.

[21]  Graeme Hirst,et al.  Race-Based Parsing and Syntactic Disambiguation , 1990, Cogn. Sci..

[22]  Michael Lebowitz,et al.  Memory-Based Parsing , 1983, Artif. Intell..

[23]  Richard L. Lewis,et al.  Integrating knowledge sources in language comprehension , 1993 .

[24]  Barr and Feigenbaum Edward A. Avron,et al.  The Handbook of Artificial Intelligence , 1981 .

[25]  Ralph Grishman,et al.  Computational linguistics : an introduction , 1986 .

[26]  Sergei Nirenburg,et al.  World Modeling for NLP , 1990 .

[27]  Lee D. Erman,et al.  A model and a system for machine recognition of speech , 1973 .

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

[29]  Sergei Nirenburg,et al.  Two Types of Adaptive MT Environments , 1994, COLING.

[30]  Roger C. Schank,et al.  Question-driven understanding: an integrated theory of story understanding, memory and learning , 1989 .

[31]  Kevin Knight,et al.  Artificial intelligence (2. ed.) , 1991 .

[32]  Christopher K. Riesbeck,et al.  Toward Completely Integrated Parsing and Inferencing , 1986 .

[33]  R. Schank,et al.  Inside Computer Understanding , 1981 .

[34]  Richard Edward Cullingford,et al.  Script application: computer understanding of newspaper stories. , 1977 .

[35]  H. Penny Nii,et al.  The Handbook of Artificial Intelligence , 1982 .

[36]  Michael G. Dyer,et al.  BORIS - An Experiment in In-Depth Understanding of Narratives , 1983, Artif. Intell..

[37]  Graeme Hirst,et al.  Semantic Interpretation and Ambiguity , 1988, Artif. Intell..

[38]  Sergei Nirenburg,et al.  Toward Multi-Engine Machine Translation , 1994, HLT.

[39]  Sergei Nirenburg,et al.  Three Heads are Better than One , 1994, ANLP.

[40]  Sergei Nirenburg,et al.  HUNTER-GATHERER: Three Search Techniques Integrated for Natural Language Semantics , 1996, AAAI/IAAI, Vol. 2.

[41]  Lawrence Birnbaum,et al.  Problems in conceptual analysis of natural language , 1979 .

[42]  Claire Cardie,et al.  A Cognitively Plausible Approach to Understanding Complex Syntax , 1991, AAAI.

[43]  Ramanathan V. Guha,et al.  Building large knowledge-based systems , 1989 .

[44]  Kavi Mahesh,et al.  Uniform Representations for Syntax-Semantics Arbitration , 1994, ArXiv.

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

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

[47]  Kavi Mahesh,et al.  Ontology Development for Machine Translation: Ideology and Methodology , 1996 .

[48]  Roger C. Schank,et al.  SCRIPTS, PLANS, GOALS, AND UNDERSTANDING , 1988 .

[49]  Richard Granger,et al.  Inference processing and error recovery in sentence understanding , 1989 .

[50]  강승식,et al.  [서평]「Electric Words : Dictionaries, Computers and Meanings」 , 1997 .

[51]  Ii Gerald Francis Dejong.  Skimming stories in real time: an experiment in integrated understanding. , 1979 .

[52]  Thomas R. Gruber,et al.  Toward principles for the design of ontologies used for knowledge sharing? , 1995, Int. J. Hum. Comput. Stud..