Learning the countability of English nouns from corpus data
Date of Issue2003
Annual Meeting of the Association for Computational Linguistics (41st : 2003)
School of Humanities and Social Sciences
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%.
© 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].