Class-based probability estimation using a semantic hierarchy.

Weir, David and Clark, Stephen (2001) Class-based probability estimation using a semantic hierarchy. In: 2nd meeting of the North American Chapter of the Association for Computational Linguistics : proceedings of the conference, June 2-7, 2001, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA. ASSOCIATION COMPUTATIONAL LINGUISTICS, San Francisco, California, pp. 95-102. ISBN 1-55860-775-7

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This paper concerns the acquisition of a particular kind of lexical knowledge, namely the knowledge of which noun senses can fill argument slots of predicates. Probabilities are used to represent the knowledge, and classes from a semantic hierarchy are used to estimate the probabilities. There is a particular focus on the problem of how to determine a suitable class, or level of generalisation, in the hierarchy. A pseudo disambiguation task is used to compare different class-based estimation methods.

Item Type: Book Section
Schools and Departments: School of Engineering and Informatics > Informatics
Depositing User: David Weir
Date Deposited: 06 Feb 2012 18:30
Last Modified: 27 Aug 2019 12:51
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