A preliminary study on the impact of lexical concreteness on word senses disambiguation

Psychologists have shown that abstract words are harder to understand and often acquired later than concrete words. In this work, we study how the difficulty of automatic word sense disambiguation (WSD) might be affected by this intrinsic property of words, namely the concreteness of a word and its individual senses. We also explore the feasibility of inducing a numerical index for sense and lexical concreteness from dictionary definitions. Analysis of system performance in previous SENSEVAL exercises suggests that concrete words are often easier to disambiguate. The high overall agreement between human ratings and definition-induced ratings is also encouraging. The concreteness factor is worth the attention of computational linguists, particularly in terms of how it bears on the differential information demand of individual words in WSD and how the knowledge of this property could be employed to fine-tune WSD systems to better deal with the lexical sensitivity of the task. © 2008 by Oi Yee Kwong.