Knowledge-based Word Sense Disambiguation using Topic Models
Table 1: Comparison of F1 scores with various WSD systems on English all-words datasets of Senseval-2, Senseval-3, SemEval-2007, SemEval-2013, SemEval-2015. WSD-TM corresponds to the proposed method. The best results in each column among knowledge-based systems are marked in bold.
['[EMPTY]', '[BOLD] System', '[BOLD] Senseval-2', '[BOLD] Senseval-3', '[BOLD] SemEval-07', '[BOLD] SemEval-13', '[BOLD] SemEval-15', '[BOLD] All']
Moro14 Zhong10 Melmaud16 set word whose context embedding is the most similar to the context embedding of the test instance.