TAILIEUCHUNG - Báo cáo khoa học: "SOLVING THEMATIC DIVERGENCES TRANSLATIONIN MACHINE"

Though most translation systems have some mechanism for translating certain types of divergent predicate-argument structures, they do not provide a genera] procedure that takes advantage of the relationship between lexical-semantic structure and syntactic structure. A divergent predicate-argument structure is one in which the predicate (., the main verb) or its arguments (., the subject and object) do not have the same syntactic ordering properties for both the source and target language. . | SOLVING THEMATIC DIVERGENCES IN MACHINE TRANSLATION Bonnie Dorr . Artificial Intelligence Laboratory 545 Technology Square Room 810 Cambridge MA 02139 USA internet bonnie@ ABSTRACT Though most translation systems have some mechanism for translating certain types of divergent predicate-argument structures they do not provide a general procedure that takes advantage of the relationship between lexical-semantic structure and syntactic structure. A divergent predicate-argument structure is one in which the predicate . the main verb or its arguments . the subject and object do not have the same syntactic ordering properties for both the source and target language. To account for such ordering differences a machine translator must consider language-specific syntactic idiosyncrasies that distinguish a target language from a source language while making use of lexical-semantic uniformities that tie the two languages together. This paper describes the mechanisms used by the UNITRAN machine translation system for mapping an underlying lexical-conceptual structure to a syntactic structure and vice versa and it shows how these mechanisms coupled with a set of general linking routines solve the problem of thematic divergence in machine translation. 1 INTRODUCTION There are a number of different divergence types that arise during the translation of a source language to a target language. Figure 1 shows some of these divergences with respect to Spanish English and We will look at each of these traditionally difficult divergence types in turn. The first divergence type is a structural divergence in that the verbal object is realized as a noun phrase John in English and as a prepositional phrase a Juan in Spanish. The second diver- This paper describes research done at the Artificial Intelligence Laboratory of the Massachusetts Institute of Technology. Support for this research has been provided by NSF Grant DCR-85552543 under a Presidential .

• Báo cáo khoa học
• SOLVING THEMATIC DIVERGENCES
• TRANSLATION IN MACHINE
• Bonnie Doff
• 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
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• Taxonomy
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• Individuals in Natural
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• The Use of Ooject Special Knowledge
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• Mark H
• Bursteln