TAILIEUCHUNG - Báo cáo khoa học: "The Role Of Focussing in Interpretation of Pronouns "

In this p;,perI [ discuss the formal relationship between the process of focussing and interpret;ition of pronominal anaphora. The discussion of focussing extends the work of Grosz [1977]. Foct,ssing is defined algorithmical]y as a process which chooses a focus of attention in a discourse and moves it around as the speaker's focus ch'mges. The paper shows how to use the focussing algorithm by ;m extended example given below. DI-I Alfred a,ld Zohar liked to play baseball. 2 They played it everyday after school before dinner. 3 After their game, the two usually went for ice cream cones. . | The Role Of Focussing in Interpretation of Pronouns Candace L. Sidner Artificial Intelligence Laboratory Massachusetts Institute of Technology Cambridge MA 02139 and Bolt Beranek and Newman Inc. 50 Moulton Street Cambridge MA 02138 In this paper I discuss the formal relationship between the process of focussing and interpretation of pronominal anaphora. The discussion of focussing extends the work of Grosz 1977 . Focussing is defined algorithmically as a process which chooses a focus of attention in a discourse and moves it around as the speaker s focus changes. The paper shows how to use the focussing algorithm by an extended example given below. Dl-1 Alfred and Zohar liked to play baseball. 2 They played it everyday after school before dinner. 3 After their game the two usually went for ice cream cones. 4 They tasted really good. 5 Alfred always had the vanilla super scooper 6 while Zohar tried the flavor of the day cone. 7 After the cones had been eaten 8 the boys went home to study. In this example the discourse focusses initially on baseball. The focus moves in Dl-3 to the ice cream cone. Using this example I show how the formal algorithm computes focus and determines how the focus moves according to the signals which the speaker uses in discourse to indicate the movement. Given a process notion of focus the paper reviews the difficulties with previous approaches Rieger 1974 Charniak 1972 Winograd 1971 Hobbs 1975 and Lockman 1978 . Briefly the first four authors all point out the need for inferencing as part of anaphora disambiguation but each of their schemes for inferencing suffer from the need for control which will reduce the combinatorial search or which will insure only one search path is taken. In addition Winograd and Lockmnn are aware of pronoun phenomena which cannot be treated strictly by inference as shown below. D2-1 I haven t seen Jeff for several days. 2 Carl thinks he s studying for his exams. 3 Oscar says he is sick 4 but I think he went to .

• Báo cáo khoa học
• The Role Of Focussing
• Interpretation of Pronouns
• Candace L
• Sidner
• 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