Hogan, Deirdre (2007) Empirical measurements of lexical similarity in noun phrase conjuncts. In: ACL 2007 - 45th Annual Meeting of the Association for Computational Linguistics, 25-27 June 2007, Prague, Czech Republic.
Abstract
The ability to detect similarity in conjunct heads is potentially a useful tool in helping to disambiguate coordination structures - a difficult task for parsers. We propose a distributional measure of similarity designed
for such a task. We then compare several different measures of word similarity by testing whether they can empirically detect similarity in the head nouns of noun phrase conjuncts
in the Wall Street Journal (WSJ) treebank. We demonstrate that several measures of word similarity can successfully detect conjunct head similarity and suggest that the measure proposed in this paper is the most appropriate for this task.
Metadata
Item Type: | Conference or Workshop Item (Paper) |
---|---|
Event Type: | Conference |
Refereed: | Yes |
Uncontrolled Keywords: | noun phrase disambiguation; |
Subjects: | Computer Science > Machine translating |
DCU Faculties and Centres: | Research Initiatives and Centres > National Centre for Language Technology (NCLT) |
Publisher: | Association for Computational Linguistics |
Official URL: | http://www.aclweb.org/anthology/P/P07/ |
Copyright Information: | © 2007 Association for Computational Linguistics |
Use License: | This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License |
Funders: | Science Foundation Ireland, SFI 04/BR/CS370 |
ID Code: | 15220 |
Deposited On: | 18 Feb 2010 11:14 by DORAS Administrator . Last Modified 19 Jul 2018 14:50 |
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