Paper: An Enhanced Lesk Word Sense Disambiguation Algorithm through a Distributional Semantic Model

ACL ID C14-1151
Title An Enhanced Lesk Word Sense Disambiguation Algorithm through a Distributional Semantic Model
Venue International Conference on Computational Linguistics
Session Main Conference
Year 2014
Authors

This paper describes a new Word Sense Disambiguation (WSD) algorithm which extends two well-known variations of the Lesk WSD method. Given a word and its context, Lesk algorithm exploits the idea of maximum number of shared words (maximum overlaps) between the context of a word and each definition of its senses (gloss) in order to select the proper meaning. The main contribution of our approach relies on the use of a word similarity function defined on a distribu- tional semantic space to compute the gloss-context overlap. As sense inventory we adopt Babel- Net, a large multilingual semantic network built exploiting both WordNet and Wikipedia. Besides linguistic knowledge, BabelNet also represents encyclopedic concepts coming from Wikipedia. The evaluation performed on SemEval-2013 Multili...