Using automatically acquired predominant senses for word sense disambiguation

McCarthy, Diana, Koeling, Rob, Weeds, Julie and Carroll, John (2004) Using automatically acquired predominant senses for word sense disambiguation. In: 3rd International Workshop on the Evaluation of Systems for the Semantic Analysis of Text (SENSEVAL), Barcelona, Spain.

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In word sense disambiguation (WSD), the heuristic of choosing the most common sense is extremely powerful because the distribution of the senses of a word is often skewed. The first (or predominant) sense heuristic assumes the availability of handtagged data. Whilst there are hand-tagged corpora available for some languages, these are relatively small in size and many word forms either do not occur, or occur infrequently. In this paper we investigate the performance of an unsupervised first sense heuristic where predominant senses are acquired automatically from raw text. We evaluate on both the SENSEVAL-2 and SENSEVAL-3 English allwords data. For accurate WSD the first sense heuristic should be used only as a back-off, where the evidence from the context is not strong enough. In this paper however, we examine the performance of the automatically acquired first sense in isolation since it turned out that the first sense taken from SemCor outperformed many systems in SENSEVAL-2.

Item Type: Conference or Workshop Item (Paper)
Schools and Departments: School of Engineering and Informatics > Informatics
Depositing User: Diana Frances McCarthy
Date Deposited: 06 Feb 2012 19:38
Last Modified: 13 Apr 2012 08:42
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