TAILIEUCHUNG - Báo cáo khoa học: "A Discourse Copying Algorithm for Ellipsis and Anaphora Resolution"

We give an analysis of ellipsis resolution in terms of a straightforward discourse copying algorithm that correctly predicts a wide range of phenomena. The treatment does not suffer from problems inherent in identity-of-relations analyses. Furthermore, in contrast to the approach of Dalrymple et al. [1991], the treatment directly encodes the intuitive distinction between full NPs and the referential elements that corefer with them through what we term role linking. | A Discourse Copying Algorithm for Ellipsis and Anaphora Resolution Andrew Kehler Harvard University Aiken Computation Laboratory 33 Oxford Street Cambridge MA 02138 kehler@ Abstract We give an analysis of ellipsis resolution in terms of a straightforward discourse copying algorithm that correctly predicts a wide range of phenomena. The treatment does not suffer from problems inherent in identity-of-relations analyses. Furthermore in contrast to the approach of Dalrymple et al. 1991 the treatment directly encodes the intuitive distinction between full NPs and the referential elements that corefer with them through what we term role linking. The correct predictions for several problematic examples of ellipsis naturally result. Finally the analysis extends directly to other discourse copying phenomena. 1 Introduction A simple example of verb phrase VP ellipsis is given in sentence 1 1 John likes his mother and Bill does too. The stranded auxiliary in the second clause indicates the deletion of a verb phrase the meaning of which is to be determined from another clause in this case the first clause. Following Dalrymple et al. 1991 we term the clause that the VP is copied from the source clause and the clause which contains the elided VP the target clause. As is well established in the literature referential elements1 in the source clause VP may give rise to strict sloppy ambiguities 1 For present purposes we will use the term referential elements as synonymous with pronouns. In Section 5 we discuss how this class may be extended to include implicit arguments as well. in the target clause for example in sentence 1 the target clause may receive one of two readings namely one in which Bill likes John s mother the strict reading and one in which Bill likes his own mother the sloppy reading . In this paper we address the distribution of strict and sloppy readings in VP-ellipsis and other anaphoric phenomena. In Section 2 we discuss problems with past .

• Báo cáo khoa học
• A Discourse Copying Algorithm
• Ellipsis and Anaphora Resolution
• Andrew Kehler
• 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