TAILIEUCHUNG - Báo cáo khoa học: "Sentence Disambiguation by a Shift-Reduce Parsing Technique"

Native speakers of English show definite and consistent preferences for certain readings of syntactically ambiguous sentences. A user of a natural-language-processing system would naturally expect it to reflect the same preferences. Thus, such systems must model in some way the linguistic performance as well as the linguistic competence of the native speaker. We have developed a parsing algorithm--a variant of the LALR(I} algorithm--that models the preference behavior of native speakers for a range of syntactic preference phenomena reported in the psycholinguistic literature, including the recent data on lexical preferences. . | Sentence Disambiguation by a Shift-Reduce Parsing Technique Stuart M. Shieber Artificial Intelligence Center SRI International 333 Ravenswood Avenue Menlo Park CA 94025 Abstract Native speakers of English show definite and consistent preferences for certain readings of syntactically ambiguous sentences. A user of a natural-language-processing system would naturally expect it to reflect the same preferences. Thus such systems must model in some way the linguistic performance as well as the linguistic competence of the native speaker. We have developed a parsing algorithm a variant of the LALR l shift-reduce algorithm that models the preference behavior of native speakers for a range of syntactic preference phenomena reported in the psycholinguistic literature including the recent data on lexical preferences. The algorithm yields the preferred parse deterministically without building multiple parse trees and choosing among them. As a side effect it displays appropriate behavior in processing the much discussed garden-path sentences. The parsing algorithm has been implemented and has confirmed the feasibility of our approach to the modeling of these phenomena. 1. Introduction For natural language processing systems to be useful they must assign the same interpretation to a given sentence that a native speaker would since that is precisely the behavior users will expect. Consider for example the case of ambiguous sentences. Native speakers of English show definite and consistent preferences for certain readings of syntactically ambiguous sentences Kimball 1973 Frailer and Fodor 1978 Ford et al. 1982 . A user of a natural-language-processing system would naturally expect it to reflect the same preferences. Thus such systems must model in some way the linguistic performance as well as the linguistic competence of the native speaker. This idea is certainly not new in the artificial-intelligence literat ure. The pioneering work of Marcus Marcus 1980 is perhaps the best .

• Báo cáo khoa học
• Sentence Disambiguation
• a Shift Reduce Parsing Technique
• Stuart M
• Shieber
• 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