Domain-specific sense distributions and predominant sense acquisition

Koeling, Rob, McCarthy, Diana and Carroll, John (2005) Domain-specific sense distributions and predominant sense acquisition. In: Joint Human Language Technology and Empirical Methods in Natural Language Processing Conferences, Vancouver, Canada.

Full text not available from this repository.


Distributions of the senses of words are often highly skewed. This fact is exploited by word sense disambiguation (WSD) systems which back off to the predominant sense of a word when contextual clues are not strong enough. The domain of a document has a strong influence on the sense distribution of words, but it is not feasible to produce large manually annotated corpora for every domain of interest. In this paper we describe the construction of three sense annotated corpora in different domains for a sample of English words. We apply an existing method for acquiring predominant sense information automatically from raw text, and for our sample demonstrate that (1) acquiring such information automatically from a mixed-domain corpus is more accurate than deriving it from SemCor, and (2) acquiring it automatically from text in the same domain as the target domain performs best by a large margin. We also show that for an all words WSD task this automatic method is best focussed on words that are salient to the domain, and on words with a different acquired predominant sense in that domain compared to that acquired from a balanced corpus.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Association for Computational Linguistics
Schools and Departments: School of Engineering and Informatics > Informatics
Depositing User: Rob Koeling
Date Deposited: 06 Feb 2012 21:13
Last Modified: 13 Apr 2012 13:57
📧 Request an update