Proceedings of the Annual Meeting of the Cognitive Science Society

Young children and natural language processing programs share an insufficient knowledge of word meanings. Children catch up by learning, using innate predisposition and observation of language use. However, no one hafi demonstrated artificial devices that robustly learn lexical semantic classifications from example sentences. This paper describes the ongoing development of such a device. A n early version discovers verbs with a non-stative sense by searching in unrestricted text for verbs in syntactic constructions forbidden to statives. Our program parses unrestricted text to the extent necessary for classification. Once the parsing is done recognizing the telltale constructions is so easy even a two-year-old child could do it. In fact, Landau and Gleitman (1985) and especially Gleitman (1989) argue that children must, can, and do use the syntactic constructions in which verbs appear to support meaning acquisition. In this paper we use our program to examine the difficulty of exploiting two particular syntactic constructions to discover the availability of non-stative senses, concluding that only very little sophistication is needed. This conclusion bolsters the general position of Gleitman (1989) that children can exploit syntactic context to aid in semantic classification of verbs.