TAILIEUCHUNG - Báo cáo khoa học: "A General Feature Space for Automatic Verb Classification"

We develop a general feature space for automatic classification of verbs into lexical semantic classes. Previous work was limited in scope by the need for manual selection of discriminating features, through a linguistic analysis of the target verb classes (Merlo and Stevenson, 2001). We instead analyze the classification structure at a higher level, using the possible defining characteristics of classes as the basis for our feature space. The general feature space achieves reductions in error rates of 42— 69%, on a wider range of classes than investigated previously, with comparable performance to feature sets manually selected for the particular. | A General Feature Space for Automatic Verb Classification Eric Joanis and Suzanne Stevenson Department of Computer Science University of Toronto joanis suzanne @ Abstract We develop a general feature space for automatic classification of verbs into lexical semantic classes. Previous work was limited in scope by the need for manual selection of discriminating features through a linguistic analysis of the target verb classes Merlo and Stevenson 2001 . We instead analyze the classification structure at a higher level using the possible defining characteristics of classes as the basis for our feature space. The general feature space achieves reductions in error rates of 4269 on a wider range of classes than investigated previously with comparable performance to feature sets manually selected for the particular classification tasks. Our results show that the approach is generally applicable and avoids the need for resource-intensive linguistic analysis for each new task. 1 Introduction Wide-coverage language processing systems require large amounts of knowledge about individual words leading to a lexical acquisition bottleneck. Because verbs play a central role in the syntactic and semantic interpretation of a sentence much research has focused on automatically learning properties of verbs from text corpora such as their subcategorization Brent 1993 Briscoe and Carroll 1997 argument roles Riloff and Schmelzenbach 1998 Gildea and Jurafsky 2002 selectional preferences Resnik 1996 and lexical semantic classification Dorr and Jones 1996 Lapata and Brew 1999 Schulte im Walde 2000 Merlo and Stevenson 2001 . Our work aims to extend the applicability of the latter by developing a general feature space for automatic verb classification. Specifically Merlo and Stevenson 2001 showed that verbs could be automatically classified into one of three lexical semantic classes on the basis of five simple statistical features. This work demonstrated the feasibility of verb .

• Báo cáo khoa học
• A General Feature Space
• Automatic Verb Classification
• Eric Joanis and Suzanne Stevenson
• 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
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• 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
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• EVEN COMPLETE
• UNGRAMHATICALITY
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• Taxonomy
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• The Use of Ooject Special Knowledge
• Natural Language Processing
• Mark H
• Bursteln