TAILIEUCHUNG - Báo cáo khoa học: "The Use of Ooject-Special Knowledge in Natural Language Processing"

it is widely reco~nlzed that the process of understandln~ natural language texts cannot be accomplished w i t h o u t accessin~ mundane Knowledge a b o u t the w o r l d [2, 4, 6, 7]. That is, in order to resolve ambiguities, form expectations, and make causal connections between events, we must make use of all sorts of episodic, stereotypic and factual knowledge. In this p a p e r , we are concerned with the way functional knowledge of objects, and associations between objects can be exploited in an understandln~ system. . | The Use of Object-Specific Knowledge in Natural Language Processing Mark H. Bursteln Department of Computer Science Yale University 1. INTRODUCTION It is widely recognized that the process of understanding natural language texts cannot be accomplished without accessing mundane knowledge about the world 2 4 6 7 . Tnat is in order to resolve ambiguities form expectations and make causal connections between events we must make use of all sorts of episodic stereotypic and factual knowledge. In this paper we are concerned with the way functional knowledge of objects and associations between objects can be exploited in an understanding system. Consider the sentence 1 John opened tne Dottle 30 he could pour the wine. Anyone reading this sentence makes assumptions about what happened which go far beyond what is stated. For example we assume without hesitation that the wine being poured came from inside the bottle. Although this seems quite obvious there are many other interpretations wnich are equally valid. John could be filling the Dottie rather than emptying the wine out of it. In fact It need not be true that the wine ever contacted the bottle. There may have been some other reason Jonn nad to open the bottle first. Yet in the absence of a larger context some causal Inference mechanism forces US as human understanders to find the common interpretation in the process of connecting these two events causally. In interpreting this sentence we also rely on an understanding of what it means for a bottle to be open . Only by using knowledge of what is possible when a bottle is open are able we understand why John had to open the bottle to pour the wine out of it. Strong associations are at work here helping US to make these connections. A sentence such as 2 John closed the bottle and poured the wine. appears to be self contradictory only because we assume that the wine was In tne bottle before applying our knowledge of open and closed bottles to the situation. Only then do we

• Báo cáo khoa học
• The Use of Ooject Special Knowledge
• Natural Language Processing
• Mark H
• Bursteln
• 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