Most work on word sense disambiguation has assumed that word usages are best labeled with a single sense. However, contextual ambiguity or fine-grained senses can potentially enable multiple sense interpretations of a usage. We present a new SemEval task for evaluating Word Sense Induction and Disambiguation systems in a setting where instances may be labeled with multiple senses, weighted by their applicability. Four teams submitted nine systems, which were evaluated in two settings.
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