Abstract
In this article, we concentrate in conceptual relations as a source of information for Word Sense Disambiguation (WSD) systems. We start with a review the most relevant research in the field, then we implement our own algorithm. As a starting point we have chosen the conceptual density algorithm of Agirre and Rigau. We generalize the original algorithm, parameterizing many aspects. This new algorithm obtains a relative improvement of 24% in terms of precision and recall. We also offer comparative evaluation of our system with respect to the participants in the SENSEVAL-2 disambiguation competition. We conclude that conceptual relations provide a source of information that is insufficient by itself to achieve good disambiguation results, but can, however, be a very accurate heuristic in a combined system.
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