Learning a Compositional Semantic Parser using an Existing Syntactic Parser (2009)
We present a new approach to learning a semantic parser (a system that maps natural language sentences into logical form). Unlike previous methods, it exploits an existing syntactic parser to produce disambiguated parse trees that drive the compositional semantic interpretation. The resulting system produces improved results on standard corpora on natural language interfaces for database querying and simulated robot control.
In Joint Conference of the 47th Annual Meeting of the Association for Computational Linguistics and the 4th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing (ACL-IJCNLP 2009), pp. 611--619, Suntec, Singapore, August 2009.

Slides (PPT)
Ruifang Ge Ph.D. Alumni grf [at] cs utexas edu
Raymond J. Mooney Faculty mooney [at] cs utexas edu