TAILIEUCHUNG - Báo cáo khoa học: "Unification-BasedSemantic Interpretation"

We show how unification can be used to specify the semantic interpretation of natural-language expressions, including problematical constructions involving long-distance dependencies. We also sketch a theoretical foundation for unificationbased semantic interpretation, and compare the unification-based approach with more conventional techniques based on the lambda calculus. Our notation uses equations of a very simple format--just ~eal;ure=value--and permits only one equation per feature per constituent, but we can indicate constraints that would be expressed in other formalisms using more complex equations by letting the value of a feature contain a variable that appears in more than one equation. . | Unification-Based Semantic Interpretation Robert c. Moore Artificial Intelligence Center SRI International Menlo Park CA 94025 Abstract We show how unification can be used to specify the semantic interpretation of natural-language expressions including problematical constructions involving long-distance dependencies. We also sketch a theoretical foundation for unificationbased semantic interpretation and compare the unification-based approach with more conventional techniques based on the lambda calculus. 1 Introduction Over the past several years unification-based formalisms Shieber 1986 have come to be widely used for specifying the syntax of natural languages particularly among computational linguists. It is less widely realized by computational linguists that unification can also be a powerful tool for specifying the semantic interpretation of natural languages. While many of the techniques described in this paper are fairly well known among natural-language researchers working with logic grammars they have not been extensively discussed in the literature perhaps the only systematic presentation being that of Perefra and Shieber 1987 . This paper goes into many issues in greater detail than do Pereira and Shieber however and sketches what may be the first theoretical analysis of unification-based semantic interpretation. We begin by reviewing the basic ideas behind unification-based grammar formalisms which will also serve to introduce the style of notation to be used throughout the paper. The notation is that used in the Core Language Engine CLE developed by SRI s Cambridge Computer Science Research Center in Cambridge England a system whose semantic-interpretation component makes use of many of the ideas presented here. Fundamentally unification grammar is a generalization of context-free phrase structure grammar in which grammatical-category expressions are not simply atomic symbols but have sets of features with constraints on their values. Such constraints

• Báo cáo khoa học
• Unification BasedSemantic Interpretation
• Robert C
• Moore
• Long Papers
• scientific reports
• model language
• process natural language
• Dialog Control
• Natural Language System
• Dialog Control in a Natural Language System
• Expanding the Horizons
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• Phil Hayes
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• NATURAL LANGUAGE SYSTEMS
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• NATURAL LANGUAGE
• INTERACTION WITH MACHINES
• 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
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• 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
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• 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
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• A LOGIC PROGRAMMING PERSPECTIVE
• Sharon C
• Salveter David Maier
• PLANNING NATURAL LANGUAGE
• EXPRESSIONS REFERRING
• Douglas E
• Appelt
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• NATURAL LANGUAGE GENERATION
• Kathleen R
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• KNOWLEDGE REPRESENTATION
• THE KEY TO THE SELECTION PROBLEM
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• Jeffrey Conklin David D
• McDonald
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• NATURAL LANGUAGE UNDERSTANDING
• Stuart C
• Shapiro
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• Natural Language Processing
• Mark H
• Bursteln