Abstract
This paper generalizes the Adapted Lesk Algorithm of Banerjee and Pedersen (2002) to a method of word sense disambiguation based on semantic relatedness. This is possible since Lesk’s original algorithm (1986) is based on gloss overlaps which can be viewed as a measure of semantic relatedness. We evaluate a variety of measures of semantic relatedness when applied to word sense disambiguation by carrying out experiments using the English lexical sample data of Senseval-2. We find that the gloss overlaps of Adapted Lesk and the semantic distance measure of Jiang and Conrath (1997) result in the highest accuracy.
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Patwardhan, S., Banerjee, S., Pedersen, T. (2003). Using Measures of Semantic Relatedness for Word Sense Disambiguation. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2003. Lecture Notes in Computer Science, vol 2588. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36456-0_24
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DOI: https://doi.org/10.1007/3-540-36456-0_24
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