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Learning a compositional semantic parser using an existing syntactic parser

Published: 02 August 2009 Publication History

Abstract

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.

References

[1]
Daniel M. Bikel. 2004. Intricacies of Collins' parsing model. Computational Linguistics, 30(4):479--511.
[2]
Patrick Blackburn and Johan Bos. 2005. Representation and Inference for Natural Language: A First Course in Computational Semantics. CSLI Publications, Stanford, CA.
[3]
Xavier Carreras and Luis Marquez. 2004. Introduction to the CoNLL-2004 shared task: Semantic role labeling. In Proc. of 8th Conf. on Computational Natural Language Learning (CoNLL-2004), Boston, MA.
[4]
Stanley F. Chen and Ronald Rosenfeld. 1999. A Gaussian prior for smoothing maximum entropy model. Technical Report CMU-CS-99-108, School of Computer Science, Carnegie Mellon University.
[5]
Mao Chen, Ehsan Foroughi, Fredrik Heintz, Spiros Kapetanakis, Kostas Kostiadis, Johan Kummeneje, Itsuki Noda, Oliver Obst, Patrick Riley, Timo Steffens, Yi Wang, and Xiang Yin. 2003. Users manual: RoboCup soccer server manual for soccer server version 7.07 and later. Available at http://sourceforge.net/projects/sserver/.
[6]
Michael Collins. 1999. Head-driven Statistical Models for Natural Language Parsing. Ph.D. thesis, University of Pennsylvania.
[7]
Ruifang Ge and Raymond J. Mooney. 2005. A statistical semantic parser that integrates syntax and semantics. In Proc. of 9th Conf. on Computational Natural Language Learning (CoNLL-2005), pages 9--16.
[8]
Ruifang Ge and Raymond J. Mooney. 2006. Discriminative reranking for semantic parsing. In Proc. of the 21st Intl. Conf. on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics (COLING/ACL-06), Sydney, Australia, July.
[9]
Daniel Gildea. 2001. Corpus variation and parser performance. In Proc. of the 2001 Conf. on Empirical Methods in Natural Language Processing (EMNLP-01), Pittsburgh, PA, June.
[10]
Rohit J. Kate and Raymond J. Mooney. 2006. Using string-kernels for learning semantic parsers. In Proc. of the 21st Intl. Conf. on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics (COLING/ACL-06), pages 913--920, Sydney, Australia, July.
[11]
Greg Kuhlmann, Peter Stone, Raymond J. Mooney, and Jude W. Shavlik. 2004. Guiding a reinforcement learner with natural language advice: Initial results in RoboCup soccer. In Proc. of the AAAI-04 Workshop on Supervisory Control of Learning and Adaptive Systems, San Jose, CA, July.
[12]
Wei Lu, Hwee Tou Ng, Wee Sun Lee, and Luke S. Zettlemoyer. 2008. A generative model for parsing natural language to meaning representations. In Proc. of the Conf. on Empirical Methods in Natural Language Processing (EMNLP-08), Honolulu, Hawaii, October.
[13]
Yusuke Miyao and Jun'ichi Tsujii. 2002. Maximum entropy estimation for feature forests. In Proc. of Human Language Technology Conf. (HLT-2002), San Diego, CA, March.
[14]
Jorge Nocedal. 1980. Updating quasi-Newton matrices with limited storage. Mathematics of Computation, 35(151):773--782, July.
[15]
Franz Josef Och and Hermann Ney. 2003. A systematic comparison of various statistical alignment models. Computational Linguistics, 29(1):19--51.
[16]
Lappoon R. Tang and Raymond J. Mooney. 2001. Using multiple clause constructors in inductive logic programming for semantic parsing. In Proc. of the 12th European Conf. on Machine Learning, pages 466--477, Freiburg, Germany.
[17]
Yuk Wah Wong and Raymond J. Mooney. 2006. Learning for semantic parsing with statistical machine translation. In Proc. of Human Language Technology Conf./N. American Chapter of the Association for Computational Linguistics Annual Meeting (HLT-NAACL-2006), pages 439--446.
[18]
Yuk Wah Wong and Raymond J. Mooney. 2007. Learning synchronous grammars for semantic parsing with lambda calculus. In Proc. of the 45th Annual Meeting of the Association for Computational Linguistics (ACL-07), pages 960--967.
[19]
Yuk Wah Wong. 2007. Learning for Semantic Parsing and Natural Language Generation Using Statistical Machine Translation Techniques. Ph.D. thesis, Department of Computer Sciences, University of Texas, Austin, TX, August. Also appears as Artificial Intelligence Laboratory Technical Report AI07-343.
[20]
John M. Zelle and Raymond J. Mooney. 1996. Learning to parse database queries using inductive logic programming. In Proc. of 13th Natl. Conf. on Artificial Intelligence (AAAI-96), pages 1050--1055.
[21]
Luke S. Zettlemoyer and Michael Collins. 2005. Learning to map sentences to logical form: Structured classification with probabilistic categorial grammars. In Proc. of the 21th Annual Conf. on Uncertainty in Artificial Intelligence (UAI-05).
[22]
Luke S. Zettlemoyer and Michael Collins. 2007. Online learning of relaxed CCG grammars for parsing to logical form. In Proc. of the 2007 Joint Conf. on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL-07), pages 678--687, Prague, Czech Republic, June.

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cover image DL Hosted proceedings
ACL '09: Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 2 - Volume 2
August 2009
595 pages
ISBN:9781932432466
  • General Chair:
  • Keh-Yih Su

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Association for Computational Linguistics

United States

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Published: 02 August 2009

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