TAILIEUCHUNG - Báo cáo khoa học: "ACQUIRING DISAMBIGUATION RULES FROM TEXT"

An effective procedure for automatically acquiring a new set of disambiguation rules for an existing deterministic parser on the basis of tagged text is presented. Performance of the automatically acquired rules is much better than the existing handwritten disambiguation rules. The success of the acquired rules depends on using the linguistic information encoded in the parser; enhancements to various components of the parser improves the acquired rule set. This work suggests a path toward more robust and comprehensive syntactic analyzers. . | ACQUIRING DISAMBIGUATION RULES FROM TEXT Donald Hindle AT T Bell Laboratories 600 Mountain Avenue Murray Hill NJ 07974-2070 Abstract An effective procedure for automatically acquiring a new set of disambiguation rules for an existing deterministic parser on the basis of tagged text is presented. Performance of the automatically acquired rules is much better than the existing handwritten disambiguation rules. The success of the acquired rules depends on using the linguistic information encoded in the parser enhancements to various components of the parser improves the ac-quừed rule set. This work suggests a path toward more robust and comprehensive syntactic analyzers. 1 Introduction One of the most serious obstacles to developing parsers to effectively analyze unrestricted English is the difficulty of creating sufficiently comprehensive grammars. While it is possible to develop toy grammars for particular theoretically interesting problems the sheer variety of forms in English together with the complexity of interaction that arises in a typical syntactic analyzer makes each enhancement of parser coverage increasingly difficult. There is no question that we are still quite far from syntactic analyzers that even begin to adequately model the grammatical variety of English. To go beyond the current generation of hand built grammars for syntactic analysis it will be necessary to develop means of acquừing some of the needed grammatical information from the regularities that appear in large corpora of naturally occurring text. This paper describes an implemented training procedure for automatically acquiring symbolic rules for a deterministic parser on the basis of unrestricted textual input. In particular I describe experiments in automatically acqmring a set of rules for disambiguation of lexical category part of speech . Performance of the acquired rule set is much better than the set of rules for lexical disambiguation written for the parser by hand over a period of

• Báo cáo khoa học
• ACQUIRING DISAMBIGUATION
• RULES FROM TEXT
• Donald Hindle
• scientific reports
• model language
• process natural language
• Dialog Control
• Natural Language System
• Dialog Control in a Natural Language System
• Expanding the Horizons
• Natural Language Interfaces
• Phil Hayes
• PROSPECTS OR PRACTICAL
• NATURAL LANGUAGE SYSTEMS
• Workshops
• NATURAL LANGUAGE
• INTERACTION WITH MACHINES
• Long Papers
• COMPUTER INTEBFACE DESIGN MURRAY TUROFF DEPARTMENT OF COMPUTER
• IiVFORMATION SCIENCE IIEW JERSEY INSTITUTE OF TECHNOLOGY
• EVALUATION OF NATURAL LANGUAGE
• INTERFACES TO DATABASE SYSTEMS
• A PANEL DISCUSSION
• database query system
• J
• Norwood Crout
• INTERFACES TO DATA BASE SYSTEMS
• Bozena Henisz
• INTERPRETING NATURAL LANGUAGE
• DATABASE UPDATES
• S
• Jermld Kaplan Jim David
• TRANSPORTABLE NATURAL LANGUAGE
• INTERFACES TO DATABASES
• Gary G
• Hendrlx and William H
• Lewis
• DATABASES THEORETICAL
• TECHNICAL ISSUES
• TRANSPORTABLE NATURAL LANGUAGE INTERFACES
• PROBLEMS AND TECHNIQUES
• Barbara J
• Grosz
• THEORETICAL TECHNICAL ISSUES
• NATURAL LANGUAGE ACCESS TO DATABASES
• R
• Petrick
• Domain Independent
• Database Access Systems
• ISSUES IN NATURAL LANGUAGE
• ACCESS TO DATABASES
• A LOGIC PROGRAMMING PERSPECTIVE
• Sharon C
• Salveter David Maier
• PLANNING NATURAL LANGUAGE
• EXPRESSIONS REFERRING
• Douglas E
• Appelt
• THE TEXT SYSTEM
• NATURAL LANGUAGE GENERATION
• Kathleen R
• M
• MENTING A DATABASE
• KNOWLEDGE REPRESENTATION
• THE KEY TO THE SELECTION PROBLEM
• E
• Jeffrey Conklin David D
• McDonald
• A KNOWLEDGE ENGINEERING
• NATURAL LANGUAGE UNDERSTANDING
• Stuart C
• Shapiro
• NATURAL LANGUAGE TEXTS
• NECESSARILY GRAMMATICAL
• EVEN COMPLETE
• UNGRAMHATICALITY
• EXTRA GRAMMATICALITY
• NATURAL LANGUAGE UNDERSTANDING SYSTEMS
• Taxonomy
• Descriptions
• Individuals in Natural
• Language Understanding
• The Use of Ooject Special Knowledge
• Natural Language Processing
• Mark H
• Bursteln