Automatic Construction of Semantic Lexicons for Learning Natural Language Interfaces (1999)
This paper describes a system, Wolfie (WOrd Learning From Interpreted Examples), that acquires a semantic lexicon from a corpus of sentences paired with semantic representations. 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.
View:
PDF, PS
Citation:
In Proceedings of the Sixteenth National Conference on Artificial Intelligence (AAAI-99), pp. 487-493, Orlando, FL, July 1999.
Bibtex:

Raymond J. Mooney Faculty mooney [at] cs utexas edu
Cynthia Thompson Ph.D. Alumni cindi [at] cs utah edu