Proceedings of the Sixth Workshop on Very Large Corpora, pp. 57-65, Montreal, Quebec, Canada, August 1998.
TR AI 98-273, Artificial Intelligence Lab, University of Texas at Austin, May 1998.
Paper ID: 89
Category: Natural Language Learning, Learning for Semantic Parsing
This paper describes a system, WOLFIE (WOrd Learning From Interpreted Examples), that acquires a semantic lexicon from a corpus of sentences paired with representations of their meaning. The lexicon learned consists of words paired with meaning representations. WOLFIE is part of an integrated system that learns to parse novel sentences into semantic representations, such as logical database queries. Experimental results are presented demonstrating WOLFIE's ability to learn useful lexicons for a database interface in four different natural languages. The lexicons learned by WOLFIE are compared to those acquired by a competing system developed by Siskind (1996).
