This paper presents recent work using the CHILL parser acquisition system to automate the construction of a natural-language interface for database queries. CHILL treats parser acquisition as the learning of search-control rules within a logic program representing a shift-reduce parser and uses techniques from Inductive Logic Programming to learn relational control knowledge. Starting with a general framework for constructing a suitable logical form, CHILL is able to train on a corpus comprising sentences paired with database queries and induce parsers that map subsequent sentences directly into executable queries. Experimental results with a complete database-query application for U.S. geography show that CHILL is able to learn parsers that outperform a pre-existing, hand-crafted counterpart. These results demonstrate the ability of a corpus-based system to produce more than purely syntactic representations. They also provide direct evidence of the utility of an empirical approach at the level of a complete natural language application.

PDF, PS

In AAAI/IAAI, pp. 1050-1055, Portland, OR, August 1996. AAAI Press/MIT Press.

@InProceedings{zelle:aaai96, title={Learning to Parse Database Queries using Inductive Logic Programming}, author={John M. Zelle and Raymond J. Mooney}, booktitle={AAAI/IAAI}, month={August}, address={Portland, OR}, publisher={AAAI Press/MIT Press}, pages={1050-1055}, url="http://www.cs.utexas.edu/users/ai-lab?zelle:aaai96", year={1996} }