Measuring word polysemousness and sense granularity at a language level

Word sense acquisition and distinction are key issues for both lexicography and lexical semantic processing. However, it is quite difficult to automatically acquire word senses and to further evaluate the results with the lexica, which more likely bear the different findings of word sense distinction and granularity. In this paper, we'd like to put forward the idea of measuring word polysemousness and sense granularity at a language level. Two methods, viz. MECBC and TIEM, are at first employed as attempts to extract Chinese word senses from the corpora. Automatic word senses mapping to the lexica and evaluation of the results are devised and realized afterwards. Our experiments shows a rather fine fitness of Chinese word polysemousness between the results and the lexica at the whole language level. Comaprison of sense granularity between different lexical semantic resources can hence be made on a sound judgment.