Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/39929
Title: Learning Semantic classes for word sense disambiguation
Authors: Kohomban, U.S.
Lee, W.S. 
Issue Date: 2005
Source: Kohomban, U.S.,Lee, W.S. (2005). Learning Semantic classes for word sense disambiguation. ACL-05 - 43rd Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference : 34-41. ScholarBank@NUS Repository.
Abstract: Word Sense Disambiguation suffers from a long-standing problem of knowledge acquisition bottleneck. Although state of the art supervised systems report good accuracies for selected words, they have not been shown to be promising in terms of scalability. In this paper, we present an approach for learning coarser and more general set of concepts from a sense tagged corpus, in order to alleviate the knowledge acquisition bottleneck. We show that these general concepts can be transformed to fine grained word senses using simple heuristics, and applying the technique for recent SENSEVAL data sets shows that our approach can yield state of the art performance. © 2005 Association for Computational Linguistics.
Source Title: ACL-05 - 43rd Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference
URI: http://scholarbank.nus.edu.sg/handle/10635/39929
ISBN: 1932432515
Appears in Collections:Staff Publications

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