Leveraging Morpho-semantics for the Discovery of Relations in Chinese Wordnet

Semantic relations of different types have played an important role in wordnet, and have been widely recognized in various fields. In recent years, with the growing interests of constructing semantic network in support of intelligent systems, automatic semantic relation discovery has become an urgent task. This paper aims to extract semantic relations relying on the in situ morpho-semantic structure in Chinese which can dispense of an outside source such as corpus or web data. Manual evaluation of thousands of word pairs shows that most relations can be successful predicted. We believe that it can serve as a valuable starting point in complementing with other approaches, which will hold promise for the robust lexical relations acquisition.