We present in this paper our submission to task 13 of SemEval2015, which makes use of background information and external resources (DBpedia and Wikipedia) to automatically disambiguate texts. Our approach follows two routes for disambiguation: one route is proposed by a state-of-the-art WSD system, and the other one by the predominant sense information extracted in an unsuper-vised way from an automatically built background corpus. We reached 4th position in terms of Fl-score in task number 13 of Se-mEval2015: "Multilingual All-Words Sense Disambiguation and Entity Linking" (Moro and Navigli, 2015). All the software and code created for this approach are publicly available on GitHub.
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