Second, we obtain distributed representations of words and relations by leveraging a novel word embedding method that considers the multi-sense nature of words and the relational knowledge among words (or their senses) contained in dictionaries.
for each polysemous word, we retrieve its number of senses from a dictionary, and conduct clustering on all its context windows in the corpus.