Joining Forces Pays Off: Multilingual Joint Word Sense Disambiguation

We present a multilingual joint approach to Word Sense Disambiguation (WSD). Our method exploits BabelNet, a very large multilingual knowledge base, to perform graphbased WSD across different languages, and brings together empirical evidence from these languages using ensemble methods. The results show that, thanks to complementing wide-coverage multilingual lexical knowledge with robust graph-based algorithms and combination methods, we are able to achieve the state of the art in both monolingual and multilingual WSD settings.