LREC 2000 - Papers

LREC 2000 2^nd International Conference on Language Resources & Evaluation

Conference Papers

Papers by paper title: A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

Papers by ID number: 1-50, 51-100, 101-150, 151-200, 201-250, 251-300, 301-350, 351-377.

List of all papers and abstracts.

Previous Paper Next Paper

Title Chinese-English Semantic Resource Construction

Authors Dorr Bonnie J. (Institute for Advanced Computer Studies, University of Maryland, bonnie@umiacs.umd.edu)
Levow Gina-Anne (Institute for Advanced Computer Studies, University of Maryland, gina@umiacs.umd.edu)
Lin Dekang (Department of Computing Science, University of Alberta, Edmonton, Alberta, Canada, T6G 2H1, lindek@cs.ualberta.ca)
Thomas Scott (Institute for Advanced Computer Studies, University of Maryland, scthmas@umiacs.umd.edu)

Keywords Chinese-English Lexicons, Lexical Acquisition, Machine Translation, Semantic Resource Construction, Thematic Roles

Session Session WO11 - Mono-Multilingual Lexicon Acquisition and Building

Abstract We describe an approach to large-scale construction of a semantic lexicon for Chinese verbs. We leverage off of three existing resources— a classification of English verbs called EVCA (English Verbs Classes and Alternations) (Levin, 1993), a Chinese conceptual database called HowNet (Zhendong, 1988c; Zhendong, 1988b; Zhendong, 1988a) (http://www .how-net.com), and a large machine-readable dic-tionary called Optilex. The resulting lexicon is used for determining appropriate word senses in applications such as machine translation and cross-language information retrieval.

="Verdana">

Title	Chinese-English Semantic Resource Construction
Authors	Dorr Bonnie J. (Institute for Advanced Computer Studies, University of Maryland, bonnie@umiacs.umd.edu) Levow Gina-Anne (Institute for Advanced Computer Studies, University of Maryland, gina@umiacs.umd.edu) Lin Dekang (Department of Computing Science, University of Alberta, Edmonton, Alberta, Canada, T6G 2H1, lindek@cs.ualberta.ca) Thomas Scott (Institute for Advanced Computer Studies, University of Maryland, scthmas@umiacs.umd.edu)
Keywords	Chinese-English Lexicons, Lexical Acquisition, Machine Translation, Semantic Resource Construction, Thematic Roles
Session	Session WO11 - Mono-Multilingual Lexicon Acquisition and Building
Abstract	We describe an approach to large-scale construction of a semantic lexicon for Chinese verbs. We leverage off of three existing resources— a classification of English verbs called EVCA (English Verbs Classes and Alternations) (Levin, 1993), a Chinese conceptual database called HowNet (Zhendong, 1988c; Zhendong, 1988b; Zhendong, 1988a) (http://www .how-net.com), and a large machine-readable dic-tionary called Optilex. The resulting lexicon is used for determining appropriate word senses in applications such as machine translation and cross-language information retrieval.