Word sense disambugation has recently been utilized in corpus-based approaches, reflecting the growth in the number of machine readable texts. One category of approaches disambiguates an input verb sense based on the similarity between its governing case fillers and those in given examples. In this paper, we introduce the degree of contribution of case to verb sense disambiguation into this existing method. In this, greater diversity of semantic range of case filler examples will lead to that case contributing to verb sense disambiguation more. We also report the result of a comparative experiment, in which the performance of disambiguation is improved by considering this notion of semantic contribution.
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