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Learning a Compositional Semantic Parser using an Existing Syntactic Parser (2009)
Ruifang Ge
and
Raymond J. Mooney
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.
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Citation:
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.
Bibtex:
@inproceedings{ge:ACL-IJCNLP09, title={Learning a Compositional Semantic Parser using an Existing Syntactic Parser}, author={Ruifang Ge and Raymond J. Mooney}, booktitle={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)}, month={August}, address={Suntec, Singapore}, pages={611--619}, url="http://www.cs.utexas.edu/users/ai-lab?ge:ACL-IJCNLP09", year={2009} }
Presentation:
Slides (PPT)
People
Ruifang Ge
Ph.D. Alumni
grf [at] cs utexas edu
Raymond J. Mooney
Faculty
mooney [at] cs utexas edu
Areas of Interest
Advice-taking Learners
Learning for Semantic Parsing
Machine Learning
Labs
Machine Learning