Handling adjectives, adverbs and words with different POS tags: To get the best out of all Word-Net similarity measures, we exploited the relationships between different forms of the terms in Word-Net to find the noun form of the terms in the entity models and pruned sentences before calculating the similarity.
the term similarity is computed by forming an ensemble using the standard WordNet similarity measures namely, WUP (Wu and Palmer, 1994), LCH (Leacock and Chodorow, 1998), Resnik (Resnik, 1995), LIN (Lin, 1998), JCN (Jiang and Conrath, 1997), as well as a predict vector-based measure Word2vec (Mikolov et al., 2013) and a morphology-based similarity metric Levenshtein 1 as: where t 1 and t 2 are input terms and M is the set of above mentioned similarity measures.