Word sense disambiguation (WSD) has been regarded as essential or necessary in many high-level NLP applications that require a certain degree of semantic interpretation, such as machine translation, information retrieval (IR) and question answering, etc.
previous investigations into the role of WSD in IR have shown that low accuracy in WSD negated any possible performance increase from ambiguity resolution [1,2].