A generative model for parsing natural language to meaning representations

EMNLP 2008 - 2008 Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference: A Meeting of SIGDAT, a Special Interest Group of the ACL

Volumn , Issue , 2008, Pages 783-792

  Lu, Wei ^a   Ng, Hwee Tou ^a   Lee, Wee Sun ^a   Zettlemoyer, Luke S ^b  

^a NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

^b MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DYNAMIC PROGRAMMING; SYNTACTICS;

DISCRIMINATIVE RERANKING; DYNAMIC PROGRAMMING TECHNIQUES; GENERATIVE MODEL; HIERARCHICAL REPRESENTATION; HIERARCHICAL STRUCTURES; NATURAL LANGUAGES; STATE-OF-THE-ART PERFORMANCE;

NATURAL LANGUAGE PROCESSING SYSTEMS;

EID: 80053273475     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.3115/1613715.1613815     Document Type: Conference Paper

References (19)

1. J. K. Baker. 1979. Trainable grammars for speech recognition. Journal of the Acoustical Society of America, 65:S132.
2. P. F. Brown, S. A. D. Pietra, V. J. D. Pietra, and R. L. Mercer. 1993. The mathematics of statistical machine translation: Parameter estimation. Computational Linguistics, 19(2):263-311.
3. M. Collins and T. Koo. 2005. Discriminative reranking or natural language parsing. Computational Linguistics, 31(1):25-70.
4. M. Collins. 2001. Ranking algorithms for named-entity extraction: boosting and the voted perceptron. In Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics (ACL 2002), pages 489-496.
5. M. Collins. 2002. Discriminative training methods for hidden Markov models: theory and experiments with perceptron algorithms. In Proceedings of the 2002 Conference on Empirical Methods in Natural Language Processing (EMNLP 2002), pages 1-8.
6. M. Collins. 2003. Head-driven statistical models for natural language parsing. Computational Linguistics, 29(4):589-637.
7. A. P. Dempster, N. M. Laird, and D. B. Rubin. 1977. Maximum likelihood from incomplete data via the EM algorithm. Journal of the Royal Statistical Society, 39(1):1-38.
8. R. Ge and R. J. Mooney. 2005. A statistical semantic arser that integrates syntax and semantics. In Proceedings of the Ninth Conference on Computational Natural Language Learning (CoNLL 2005), pages 9-16.
9. R. Ge and R. J. Mooney. 2006. Discriminative reranking or semantic parsing. In Proceedings of the 21st International Conference on Computational Linguistics and the 44th Annual Meeting of the Association for Computational Linguistics (COLING/ACL 2006), pages 263-270.
10. R. J. Kate and R. J. Mooney. 2006. Using string-kernels for learning semantic parsers. In Proceedings of the 21st International Conference on Computational Linguistics and the 44th Annual Meeting of the Association for Computational Linguistics (COLING/ACL 2006), pages 913-920.
11. R. J. Kate, Y. W. Wong, and R. J. Mooney. 2005. Learning to transform natural to formal languages. In Proceedings of the Twentieth National Conference on Artificial Intelligence (AAAI 2005), pages 1062-1068.
12. S. Katz. 1987. Estimation of probabilities from sparse data for the language model component of a speech recognizer. IEEE Transactions on Acoustics, Speech, and Signal Processing, 35(3):400-401.
13. L. R. Tang and R. J. Mooney. 2001. Using multiple clause constructors in inductive logic programming for semantic parsing. In Proceedings of the 12th European Conference on Machine Learning (ECML 2001), pages 466-477.
14. Y. W. Wong and R. J. Mooney. 2006. Learning for semantic parsing with statistical machine translation. In Proceedings of the Human Language Technology onference of the North American Chapter of the Association for Computational Linguistics (HLT-NAACL 2006), pages 439-446.
15. Y. W. Wong and R. J. Mooney. 2007. Learning synchronous grammars for semantic parsing with lambda calculus. In Proceedings of the 45th Annual Meeting of the Association for Computational Linguistics (ACL 2007), pages 960-967.
16. Y. W. Wong. 2007. Learning for Semantic Parsing and Natural Language Generation Using Statistical Machine Translation Techniques. Ph.D. thesis, The University of Texas at Austin.
17. K. Yamada and K. Knight. 2001. A syntax-based statistical translation model. In Proceedings of the 39th Annual Meeting of the Association for Computational Linguistics, pages 523-530.
18. L. S. Zettlemoyer and M. Collins. 2005. Learning to map sentences to logical form: Structured classification with probabilistic categorial grammars. In Proceedings of the 21st Conference on Uncertainty in Artificial Intelligence.
19. L. S. Zettlemoyer and M. Collins. 2007. Online learning of relaxed CCG grammars for parsing to logical form. In Proceedings of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLPCoNLL 2007), pages 678-687.