Thus, word sense disambiguation is a necessary component for many applications in Computational Linguistics, such as machine translation, information retrieval, information extraction, or question answering.
most of the WSD approaches reported so far rely on supervised learning techniques, relying on the data sets provided by the SensEval 1 and SemEval 2 competitions.