TAILIEUCHUNG - Báo cáo khoa học: "DISCOURSE DEIXIS: REFERENCE TO DISCOURSE SEGMENTS"

Computational approaches to discourse understanding have a two-part goal: (1) to identify those aspects of terms referm here, meaning "refer in a model", and referentm, for the entity in the model picked out by the linguistic expression. The basic features of a discourse entity are that (a) it is a constant within the current discourse model and that Co) one can attribute to it, inter alia, properties and relationships with other entities. (It is for this reason that Bill Woods once called them "conceptual coat hooks".) In some theories, different parts of the discourse model (often called spaces) may represent. | DISCOURSE DEIXIS REFERENCE TO DISCOURSE SEGMENTS Bonnie Lynn Webber Department of Computer Information Science University of Pennsylvania Philadelphia PA 19104-6389 ABSTRACT Computational approaches to discourse understanding have a two-part goal 1 to identify those aspects of discourse understanding that require process-based accounts and 2 to characterize the processes and data structures they involve. To date in the area of reference process-based accounts have been developed for subsequent reference via anaphoric pronouns and reference via definite descriptors. In this paper I propose and argue for a process-based account of subsequent reference via deictic expressions. A significant feature of this account is that it attributes distinct mental reality to units of text often called discourse segments a reality that is distinct from that of the entities described therein. 1. INTRODUCTION There seem to be at least two constructs that most current theories of discourse understanding have adopted in at least some form. The first is the discourse entity first introduced by Lauri Kartunnen in 1976 under the name discourse referent 9 and employed under various other names by many researchers including myself 18 . The other is the discourse segment. Discourse entities provide these theories with a uniform way of explaining what it is that noun phrases NP and pronouns in a discourse refer to. Some NPs evoke a new discourse entity in the listener s evolving model of the discourse which I have called simply a discourse model others refer to ones that are already there. Such entities may coưespond to something in the outside world but they do not have to. To avoid confusion with a sense of referring in the outside world I will use the terms referm here meaning refer in a model and referentm for the entity in the model picked out by the linguistic expression. The basic features of a discourse entity are that a it is a constant within the current discourse model and that b .

• Báo cáo khoa học
• DISCOURSE DEIXIS
• REFERENCE TO DISCOURSE SEGMENTS
• Bonnie Lynn Webber
• 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