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Title:
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Learning the countability of English nouns from corpus data.
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Author:
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Baldwin, Timothy.; Bond, Francis.
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Copyright year:
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2003 |
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Abstract:
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This paper describes a method for learning
the countability preferences of English
nouns from raw text corpora. The method
maps the corpus-attested lexico-syntactic
properties of each noun onto a feature
vector, and uses a suite of memory-based
classifiers to predict membership in 4
countability classes. We were able to assign
countability to English nouns with a
precision of 94.6%. |
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Subject:
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DRNTU::Humanities::Linguistics::Sociolinguistics::Computational linguistics. |
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Type:
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Conference Paper |
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Conference name:
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41st Annual Meeting of the Association for Computational Linguistics: ACL-2003 |
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School:
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School of Humanities and Social Sciences |
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Rights:
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© 2003 ACL. This is the author created version of a work that has been peer reviewed and accepted for publication by Proceedings of 41st Annual Meeting of the Association for Computational Linguistics: ACL-2003, Association for Computational Linguistics. It incorporates referee’s comments but changes resulting from the publishing process, such as copyediting, structural formatting, may not be reflected in this document. The published version is available at: [DOI: http://dx.doi.org/10.3115/1075096.1075155]. |
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Version:
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Accepted version |
