In this presentation will explore the closed world of language as a system of word relations. Words and texts are highly ambiguous, but we believe the complete
scope and complexity of this ambiguity is not well defined yet. The goal is to more properly define the problem and find the optimal solution given the vast volumes of textual data that are available.
Most of the WSD systems are not tacking properly the problem and the context is not being modelled in a proper way. Besides to this, lately WSD has been changed from a purely lexical approach
(static view) to a reference approach (dynamic view). Considering these two facts, the role of the background and discourse information is crucial.
To prove our hypothesis about what WSD systems are not facing properly, we performed an error analysis on the participant outputs of the SensEval/SemEval WSD competitions. Interesting and
surprising conclusions came out of this analysis.
Finally, our participation on the last SemEval-2015 task 13: Multilingual All-Words WSD and Entity Linking. In our system we implement our ideas about using background information to perform WSD.