An Information Retrieval Approach to Sense Ranking
Mirella Lapata, Frank Keller · Edinburgh Research Explorer (University of Edinburgh) · 2007
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.