Learning for Semantic Parsing
Semantic parsing is the process of mapping a natural-language sentence into a formal representation of its meaning. A shallow form of semantic representation is a case-role analysis (a.k.a. a semantic role labeling), which identifies roles such as agent, patient, source, and destination. A deeper semantic analysis provides a representation of the sentence in predicate logic or other formal language which supports automated reasoning. We have developed methods for automatically learning semantic parsers from annotated corpora using inductive logic programming and other learning methods. We have explored learning semantic parsers for mapping natural-language sentences to case-role analyses, formal database queries, and formal command languages (i.e. the Robocup coaching language for use in advice-taking learners). We have also explored methods for learning semantic lexicons, i.e. databases of words or phrases paired with one or more alternative formal meaning representations. Semantic lexicons can also be learned from semantically annotated sentences and are an important source of knowledge for semantic parsing. Learning for semantic parsing is part of our research on natural language learning.

"The fish trap exists because of the fish. Once you've gotten the fish you can forget the trap. The rabbit snare exists because of the rabbit. Once you've gotten the rabbit, you can forget the snare. Words exist because of meaning. Once you've gotten the meaning, you can forget the words. Where can I find a man who has forgotten words so I can talk with him?"
-- The Writings of Chuang Tzu, 4th century B.C. (Original text in Chinese)

Demos of learned natural-language database interfaces:

Tutorial on semantic parsing presented at ACL 2010:

Bishal Barman Formerly affiliated Ph.D. Student bbarman [at] apple com
Joohyun Kim Ph.D. Alumni scimitar [at] cs utexas edu
     [Expand to show all 54][Minimize]
Semantic Parsing using Distributional Semantics and Probabilistic Logic 2014
Islam Beltagy, Katrin Erk, and Raymond Mooney, In Proceedings of ACL 2014 Workshop on Semantic Parsing (SP-2014), pp. 7--11, Baltimore, MD, June 2014.
Adapting Discriminative Reranking to Grounded Language Learning 2013
Joohyun Kim and Raymond J. Mooney, In Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (ACL-2013), pp. 218--227, Sofia, Bulgaria, August 2013.
Grounded Language Learning Models for Ambiguous Supervision 2013
Joo Hyun Kim, PhD Thesis, Department of Computer Science, University of Texas at Austin.
Generative Models of Grounded Language Learning with Ambiguous Supervision 2012
Joohyun Kim, Technical Report, PhD proposal, Department of Computer Science, The University of Texas at Austin.
Learning Language from Ambiguous Perceptual Context 2012
David L. Chen, PhD Thesis, Department of Computer Science, University of Texas at Austin. 196.
Unsupervised PCFG Induction for Grounded Language Learning with Highly Ambiguous Supervision 2012
Joohyun Kim and Raymond J. Mooney, In Proceedings of the Conference on Empirical Methods in Natural Language Processing and Natural Language Learning (EMNLP-CoNLL '12), pp. 433--444, Jeju Island, Korea, July 2012.
Learning to Interpret Natural Language Navigation Instructions from Observations 2011
David L. Chen and Raymond J. Mooney, Proceedings of the 25th AAAI Conference on Artificial Intelligence (AAAI-2011) (2011), pp. 859-865.
Generative Alignment and Semantic Parsing for Learning from Ambiguous Supervision 2010
Joohyun Kim and Raymond J. Mooney, In Proceedings of the 23rd International Conference on Computational Linguistics (COLING 2010), pp. 543--551, Beijing, China, August 2010.
Learning for Semantic Parsing Using Statistical Syntactic Parsing Techniques 2010
Ruifang Ge, PhD Thesis, Department of Computer Science, University of Texas at Austin. 165 pages.
Training a Multilingual Sportscaster: Using Perceptual Context to Learn Language 2010
David L. Chen, Joohyun Kim, Raymond J. Mooney, Journal of Artificial Intelligence Research, Vol. 37 (2010), pp. 397--435.
Learning a Compositional Semantic Parser using an Existing Syntactic Parser 2009
Ruifang Ge and Raymond J. Mooney, 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 ...
Learning Language from Perceptual Context 2009
David L. Chen, unpublished. Ph.D. proposal, Department of Computer Sciences, University of Texas at Austin.
A Dependency-based Word Subsequence Kernel 2008
Rohit J. Kate, In Proceedings of the conference on Empirical Methods in Natural Language Processing (EMNLP-2008), pp. 400--409, Waikiki, Honolulu, Hawaii, October 2008.
Learning to Sportscast: A Test of Grounded Language Acquisition 2008
David L. Chen and Raymond J. Mooney, In Proceedings of the 25th International Conference on Machine Learning (ICML), Helsinki, Finland, July 2008.
Transforming Meaning Representation Grammars to Improve Semantic Parsing 2008
Rohit J. Kate, In Proceedings of the Twelfth Conference on Computational Natural Language Learning (CoNLL-2008), pp. 33--40, Manchester, UK, August 2008.
Generation by Inverting a Semantic Parser That Uses Statistical Machine Translation 2007
Yuk Wah Wong and Raymond J. Mooney, In Proceedings of Human Language Technologies: The Conference of the North American Chapter of the Association for Computational Linguistics (NAACL-HLT-07), pp. 172-179, Rochester, NY 2007.
Learning for Semantic Parsing 2007
Raymond J. Mooney, In Computational Linguistics and Intelligent Text Processing: Proceedings of the 8th International Conference (CICLing 2007), A. Gelbukh (Eds.), pp. 311--324, Mexico City, Mexico, February 2007...
Learning for Semantic Parsing and Natural Language Generation Using Statistical Machine Translation Techniques 2007
Yuk Wah Wong, PhD Thesis, Department of Computer Sciences, University of Texas at Austin. 188 pages. Also appears as Technical Report AI07-343, Artificial Intelligence Lab, University of Texas at Austin, August 200...
Learning for Semantic Parsing with Kernels under Various Forms of Supervision 2007
Rohit J. Kate, PhD Thesis, Department of Computer Sciences, University of Texas at Austin. 159 pages.
Learning Language Semantics from Ambiguous Supervision 2007
Rohit J. Kate and Raymond J. Mooney, In Proceedings of the 22nd Conference on Artificial Intelligence (AAAI-07), pp. 895-900, Vancouver, Canada, July 2007.
Learning Synchronous Grammars for Semantic Parsing with Lambda Calculus 2007
Yuk Wah Wong and Raymond J. Mooney, In Proceedings of the 45th Annual Meeting of the Association for Computational Linguistics (ACL-2007), Prague, Czech Republic, June 2007.
Semi-Supervised Learning for Semantic Parsing using Support Vector Machines 2007
Rohit J. Kate and Raymond J. Mooney, In Proceedings of the Human Language Technology Conference of the North American Chapter of the Association for Computational Linguistics, Short Papers (NAACL/HLT-2007), pp. 81--84, Rochester...
Discriminative Reranking for Semantic Parsing 2006
Ruifang Ge and Raymond J. Mooney, In Proceedings of the 21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics (COLING/ACL-06), Sydney, Australia, Jul...
Learning for Semantic Parsing with Statistical Machine Translation 2006
Yuk Wah Wong and Raymond J. Mooney, In Proceedings of Human Language Technology Conference / North American Chapter of the Association for Computational Linguistics Annual Meeting (HLT-NAACL-06), pp. 439-446, New York City, NY 20...
Learning Semantic Parsers Using Statistical Syntactic Parsing Techniques 2006
Ruifang Ge, unpublished. Doctoral Dissertation Proposal, University of Texas at Austin" , year="2006.
Using String-Kernels for Learning Semantic Parsers 2006
Rohit J. Kate and Raymond J. Mooney, In ACL 2006: Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the ACL, pp. 913-920, Morristown, NJ, USA 2006. Association for Computa...
A Kernel-based Approach to Learning Semantic Parsers 2005
Rohit J. Kate, unpublished. Doctoral Dissertation Proposal, University of Texas at Austin.
A Statistical Semantic Parser that Integrates Syntax and Semantics 2005
Ruifang Ge and Raymond J. Mooney, In Proceedings of CoNLL-2005, Ann Arbor, Michigan, June 2005.
Learning for Semantic Parsing Using Statistical Machine Translation Techniques 2005
Yuk Wah Wong, unpublished. Doctoral Dissertation Proposal, University of Texas at Austin.
Learning to Transform Natural to Formal Languages 2005
Rohit J. Kate, Yuk Wah Wong and Raymond J. Mooney, In Proceedings of the Twentieth National Conference on Artificial Intelligence (AAAI-05), pp. 1062-1068, Pittsburgh, PA, July 2005.
Learning Semantic Parsers: An Important But Under-Studied Problem 2004
Raymond J. Mooney, In Papers from the AAAI 2004 Spring Symposium on Language Learning: An Interdisciplinary Perspective, pp. 39--44, Stanford, CA, March 2004.
Learning Transformation Rules for Semantic Parsing 2004
Rohit J. Kate, Yuk Wah Wong, Ruifang Ge, and Raymond J. Mooney, unpublished. Unpublished Technical Report.
Acquiring Word-Meaning Mappings for Natural Language Interfaces 2003
Cynthia A. Thompson and Raymond J. Mooney, Journal of Artificial Intelligence Research, Vol. 18 (2003), pp. 1-44.
Integrating Top-down and Bottom-up Approaches in Inductive Logic Programming: Applications in Natural Language Processing and Relational Data Mining 2003
Lappoon R. Tang, PhD Thesis, Department of Computer Sciences, University of Texas.
Using Multiple Clause Constructors in Inductive Logic Programming for Semantic Parsing 2001
Lappoon R. Tang and Raymond J. Mooney, In Proceedings of the 12th European Conference on Machine Learning, pp. 466-477, Freiburg, Germany 2001.
Automated Construction of Database Interfaces: Integrating Statistical and Relational Learning for Semantic Parsing 2000
Lappoon R. Tang and Raymond J. Mooney, In Proceedings of the Joint SIGDAT Conference on Empirical Methods in Natural Language Processing and Very Large Corpora(EMNLP/VLC-2000), pp. 133-141, Hong Kong, October 2000.
Integrating Statistical and Relational Learning for Semantic Parsing: Applications to Learning Natural Language Interfaces for Databases 2000
Lappoon R. Tang, unpublished. Ph.D. proposal, Department of Computer Sciences, University of Texas at Austin.
Learning for Semantic Interpretation: Scaling Up Without Dumbing Down 2000
Raymond J. Mooney, In Workshop Notes for the Workshop on Learning Language in Logic, pp. 7-15, Bled, Slovenia 2000.
Active Learning for Natural Language Parsing and Information Extraction 1999
Cynthia A. Thompson, Mary Elaine Califf and Raymond J. Mooney, In Proceedings of the Sixteenth International Conference on Machine Learning (ICML-99), pp. 406-414, Bled, Slovenia, June 1999.
Automatic Construction of Semantic Lexicons for Learning Natural Language Interfaces 1999
Cynthia A. Thompson and Raymond J. Mooney, In Proceedings of the Sixteenth National Conference on Artificial Intelligence (AAAI-99), pp. 487-493, Orlando, FL, July 1999.
Semantic Lexicon Acquisition for Learning Natural Language Interfaces 1998
Cynthia Ann Thompson, PhD Thesis, Department of Computer Sciences, University of Texas at Austin. 101 pages. Also appears as Technical Report AI 99-278, Artificial Intelligence Lab, University of Texas at Austin.
Semantic Lexicon Acquisition for Learning Natural Language Interfaces 1998
Cynthia A. Thompson and Raymond J. Mooney, In Proceedings of the Sixth Workshop on Very Large Corpora, Montreal, Quebec, Canada, August 1998. Also available as TR AI 98-273, Artificial Intelligence Lab, University of Texas at Austin, M...
An Inductive Logic Programming Method for Corpus-based Parser Construction 1997
John M. Zelle and Raymond J. Mooney, unpublished. Unpublished Technical Note.
Learning to Parse Natural Language Database Queries into Logical Form 1997
Cynthia A. Thompson, Raymond J. Mooney, and Lappoon R. Tang, In Proceedings of the ML-97 Workshop on Automata Induction, Grammatical Inference, and Language Acquisition, Nashville, TN, July 1997.
Semantic Lexicon Acquisition for Learning Parsers 1997
Cynthia A. Thompson and Raymond J. Mooney, unpublished. Submitted for review.
Corpus-Based Lexical Acquisition For Semantic Parsing 1996
Cynthia Thompson, unpublished. Ph.D. proposal.
Inductive Logic Programming for Natural Language Processing 1996
Raymond J. Mooney, In Inductive Logic Programming: Selected papers from the 6th International Workshop, Stephen Muggleton (Eds.), pp. 3-22, Berlin 1996. Springer Verlag.
Learning to Parse Database Queries using Inductive Logic Programming 1996
John M. Zelle and Raymond J. Mooney, In AAAI/IAAI, pp. 1050-1055, Portland, OR, August 1996. AAAI Press/MIT Press.
Lexical Acquisition: A Novel Machine Learning Problem 1996
Cynthia A. Thompson and Raymond J. Mooney, Technical Report, Artificial Intelligence Lab, University of Texas at Austin.
A Comparison of Two Methods Employing Inductive Logic Programming for Corpus-based Parser Constuction 1995
John M. Zelle and Raymond J. Mooney, In Working Notes of the IJCAI-95 Workshop on New Approaches to Learning for Natural Language Processing, pp. 79--86, Montreal, Quebec, Canada, August 1995.
Acquisition of a Lexicon from Semantic Representations of Sentences 1995
Cynthia A. Thompson, In Proceedings of the 33rd Annual Meeting of the Association for Computational Linguistics (ACL-95), pp. 335-337, Cambridge, MA 1995.
Using Inductive Logic Programming to Automate the Construction of Natural Language Parsers 1995
John M. Zelle, PhD Thesis, Department of Computer Sciences, The University of Texas at Austin.
Learning Search-Control Heuristics for Logic Programs: Applications to Speedup Learning and Language Acquisition 1993
John M. Zelle, unpublished. Ph.D. proposal, Department of Computer Sciences, University of Texas at Austin.
Learning Semantic Grammars With Constructive Inductive Logic Programming 1993
John M. Zelle and Raymond J. Mooney, In Proceedings of the 11th National Conference on Artificial Intelligence, pp. 817-822 1993. Menlo Park, CA: AAAI Press.