An Information Retrieval Approach to Sense Ranking

Research output: Chapter in Book/Report/Conference proceedingConference contribution


In word sense disambiguation, choosing the most frequent sense for an ambiguous word is a powerful heuristic. However, its usefulness is restricted by the availability of sense-annotated data. In this paper, we propose an information retrieval-based method for sense ranking that does not require
annotated data. The method queries an information retrieval engine to estimate
the degree of association between a word and its sense descriptions. Experiments on the Senseval test materials yield state-ofthe-art performance.We also show that the estimated sense frequencies correlate reliably with native speakers’ intuitions.
Original languageEnglish
Title of host publicationHuman Language Technology Conference of the North American Chapter of the Association of Computational Linguistics, Proceedings, April 22-27, 2007, Rochester, New York, USA
Number of pages9
Publication statusPublished - 2007


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