TAILIEUCHUNG - Báo cáo khoa học: "Experiments on the Choice of Features for Learning Verb Classes"

The choice of verb features is crucial for the learning of verb classes. This paper presents clustering experiments on 168 German verbs, which explore the relevance of features on three levels of verb description, purely syntactic frame types, prepositional phrase information and selectional preferences. In contrast to previous approaches concentrating on the sparse data problem, we present evidence for a linguistically defined limit on the usefulness of features which is driven by the idiosyncratic properties of the verbs and the specific attributes of the desired verb classification. . | Experiments on the Choice of Features for Learning Verb Classes Sabine Schulte im Walde Institut fur Maschinelle Sprachverarbeitung Universitãt Stuttgart AzenbergstraBe 12 70174 Stuttgart Germany schulte@ Abstract The choice of verb features is crucial for the learning of verb classes. This paper presents clustering experiments on 168 German verbs which explore the relevance of features on three levels of verb description purely syntactic frame types prepositional phrase information and selectional preferences. In contrast to previous approaches concentrating on the sparse data problem we present evidence for a linguistically dehned limit on the usefulness of features which is driven by the idiosyncratic properties of the verbs and the specific attributes of the desired verb classification. 1 Introduction The verb is central to the meaning and the structure of a sentence and lexical verb information represents the core in supporting NLP-tasks such as word sense disambiguation Dorr and Jones 1996 Prescher et al. 2000 machine translation Dorr 1997 document classification Kla-vans and Kan 1998 and subcategorisation acquisition and filtering Korhonen 2002 . A means to generalise over and predict common properties of verbs is captured by the constitution of verb classes. Levin 1993 has established an extensive manual classification for English verbs computational approaches adopt the linguistic hypothesis that verb meaning components to a certain extent determine verb behaviour as basis for automatically inducing semantic verb classes from corpusbased features Schulte im Walde 2000 Merlo and Stevenson 2001 Joanis 2002 . Computational approaches on verb classification which take advantage of corpus-based and knowledge-based verb information offered by available tools and resources such as statistical parsers and semantic ontologies suffer from severe problems to encode and benefit from the information especially with respect to selec-tional .

• Báo cáo khoa học
• Experiments on the Choice of Features
• Learning Verb Classes
• Sabine Schulte
• 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
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• NATURAL LANGUAGE SYSTEMS
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• 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
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• 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
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• Mark H
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