Towards robust semantic role labeling

Computational Linguistics

Volumn 34, Issue 2, 2008, Pages 289-310

  Pradhan, Sameer S ^a   Ward, Wayne ^b   Martin, James H ^b  

^a BBN TECHNOLOGIES   (United States)

^b UNIVERSITY OF COLORADO   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

SEMANTICS;

ARGUMENT IDENTIFICATIONS; CLASSIFICATION TASKS; SEMANTIC ROLE LABELING; STATE OF THE ART; STRUCTURAL FEATURE; TRAINING AND TESTING; WALL STREET JOURNAL;

CLASSIFICATION (OF INFORMATION);

EID: 45749105974     PISSN: 08912017     EISSN: 15309312     Source Type: Journal    
DOI: 10.1162/coli.2008.34.2.289     Document Type: Article

References (36)

1. Bacchiani, Michiel, Michael Riley, Brian Roark, and Richard Sproat. 2006. MAP adaptation of stochastic grammars. Computer Speech and Language, 20(1):41-68.
2. Bikel, Daniel M., Richard Schwartz, and Ralph M. Weischedel. 1999. An algorithm that learns what's in a name. Machine Learning, 34:211-231.
3. Burges, Christopher J. C. 1998. A tutorial on support vector machines for pattern recognition. Data Mining and Knowledge Discovery, 2(2):121-167.
4. Carreras, Xavier and Llu?́s Màrquez. 2004. Introduction to the CoNLL-2004 shared task: Semantic role labeling. In Proceedings of the Eighth Conference on Computational Natural Language Learning (CoNLL), pages 89-97, Boston, MA.
5. Carreras, Xavier and Llu?́s Màrquez. 2005. Introduction to the CoNLL-2005 shared task: Semantic role labeling. In Proceedings of the Ninth Conference on Computational Natural Language Learning (CoNLL), pages 152-164, Ann Arbor, MI.
6. Charniak, Eugene and Mark Johnson. 2005. Coarse-to-fine n-best parsing and maxent discriminative reranking. In Proceedings of the 43rd Annual Meeting of the Association for Computational Linguistics (ACL), Ann Arbor, MI.
7. Gildea, Daniel and Daniel Jurafsky. 2002. Automatic labeling of semantic roles. Computational Linguistics, 28(3):245-288.
8. Hacioglu, Kadri, Sameer Pradhan, Wayne Ward, James Martin, and Daniel Jurafsky. 2004. Semantic role labeling by tagging syntactic chunks. In Proceedings of the Eighth Conference on Computational Natural Language Learning (CoNLL), Boston, MA.
9. Harabagiu, Sanda, Cosmin Adrian Bejan, and Paul Morarescu. 2005. Shallow semantics for relation extraction. In Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence (IJCAI), pages 1061-1067, Edinburgh, Scotland.
10. Hofmann, Thomas and Jan Puzicha. 1998. Statistical models for co-occurrence data. Memo, Massachusetts Institute of Technology Artificial Intelligence Laboratory, Cambridge, MA.
11. Jiang, Zheng Ping, Jia Li, and Hwee Tou Ng. 2005. Semantic argument classification exploiting argument interdependence. In Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence (IJCAI), pages 1067-1072, Edinburgh, Scotland.
12. Joachims, Thorsten. 1998. Text categorization with support vector machines: Learning with many relevant features. In Proceedings of the European Conference on Machine Learning (ECML), pages 137-142, Chemnitz, Germany.
13. Koomen, Peter, Vasin Punyakanok, Dan Roth, and Wen-tau Yih. 2005. Generalized inference with multiple semantic role labeling systems. In Proceedings of the Ninth Conference on Computational Natural Language Learning (CoNLL), pages 181-184, Ann Arbor, MI.
14. Kučera, Henry and W. Nelson Francis. 1967. Computational Analysis of Present-day American English. Brown University Press, Providence, RI.
15. Kudo, Taku and Yuji Matsumoto. 2000. Use of support vector learning for chunk identification. In Proceedings of the Fourth Conference on Computational Natural Language Learning (CoNLL), pages 142-144, Lisbon, Portugal.
16. Kudo, Taku and Yuji Matsumoto. 2001. Chunking with support vector machines. In Proceedings of the Second Meeting of the North American Chapter of the Association for Computational Linguistics (NAACL), Pittsburgh, PA.
17. Lin, Dekang. 1998. Automatic retrieval and clustering of similar words. In Proceedings of the Seventeenth International Conference on Computational Linguistics and Thirty Sixth Annual Meeting of the Association of Computational Linguistics (COLING/ACL), pages 768-774, Montreal, Canada.
18. Lodhi, Huma, Craig Saunders, John Shawe-Taylor, Nello Cristianini, and Chris Watkins. 2002. Text classification using string kernels. Journal of Machine Learning Research, 2(Feb):419-444.
19. Marcus, Mitchell P., Beatrice Santorini, and Mary Ann Marcinkiewicz. 1993. Building a large annotated corpus of English: The Penn treebank. Computational Linguistics, 19(2):313-330.
20. Màrquez, Lluís, Mihai Surdeanu, Pere Comas, and Jordi Turmo. 2005. A robust combination strategy for semantic role labeling. In Proceedings of the Human Language Technology Conference and Conference on Empirical Methods in Natural Language Processing (HLT/EMNLP), pages 644-651, Vancouver, British Columbia.
21. McClosky, David, Eugene Charniak, and Mark Johnson. 2006a. Effective self-training for parsing. In Proceedings of the Human Language Technology Conference/North American Chapter of the Association of Computational Linguistics (HLT/NAACL), pages 152-159, New York, NY.
22. McClosky, David, Eugene Charniak, and Mark Johnson. 2006b. Reranking and self-training for parser adaptation. In Proceedings of the Twenty First International Conference on Computational Linguistics and Forty Fourth Annual Meeting of the Association for Computational Linguistics (COLING/ACL), pages 337-344, Sydney, Australia.
23. Moschitti, Alessandro. 2006. Syntactic kernels for natural language learning: The semantic role labeling case. In Proceedings of the Human Language Technology Conference/North American Chapter of the Association of Computational Linguistics (HLT/NAACL), pages 97-100, New York, NY.
24. Musillo, Gabriele and Paola Merlo. 2006. Accurate parsing of the proposition bank. In Proceedings of the Human Language Technology Conference/North American Chapter of the Association of Computational Linguistics (HLT/NAACL), pages 101-104, New York, NY.
25. Narayanan, Srini and Sanda Harabagiu. 2004. Question answering based on semantic structures. In Proceedings of the International Conference on Computational Linguistics (COLING), pages 693-701, Geneva, Switzerland.
26. Palmer, Martha, Daniel Gildea, and Paul Kingsbury. 2005. The Proposition Bank: An annotated corpus of semantic roles. Computational Linguistics, 31(1):71-106.
27. Platt, John. 2000. Probabilities for support vector machines. In A. Smola, P. Bartlett, B. Scholkopf, and D. Schuurmans, editors, Advances in Large Margin Classifiers. MIT Press, Cambridge, MA, pages 61-74.
28. Pradhan, Sameer, Kadri Hacioglu, Valerie Krugler, Wayne Ward, James Martin, and Dan Jurafsky. 2005. Support vector learning for semantic argument classification. Machine Learning Journal, 60(1):11-39.
29. Pradhan, Sameer, Wayne Ward, Kadri Hacioglu, James Martin, and Dan Jurafsky. 2004. Shallow semantic parsing using support vector machines. In Proceedings of the Human Language Technology Conference/ North American Chapter of the Association of Computational Linguistics (HLT/NAACL), pages 233-240, Boston, MA.
30. Pradhan, Sameer, Wayne Ward, Kadri Hacioglu, James Martin, and Dan Jurafsky. 2005. Semantic role labeling using different syntactic views. In Proceedings of the Forty-Third Annual Meeting of the Association for Computational Linguistics (ACL), pages 581-588, Ann Arbor, MI.
31. Punyakanok, Vasin, Dan Roth, Wen tau Yih, and Dav Zimak. 2005. Learning and inference over constrained output. In Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence (IJCAI), pages 1117-1123, Edinburgh, Scotland.
32. Surdeanu, Mihai, Sanda Harabagiu, John Williams, and Paul Aarseth. 2003. Using predicate-argument structures for information extraction. In Proceedings of the Forty-First Annual Meeting of the Association for Computational Linguistics (ACL), pages 8-15, Sapporo, Japan.
33. Toutanova, Kristina, Aria Haghighi, and Christopher Manning. 2005. Joint learning improves semantic role labeling. In Proceedings of the Forty-Third Annual Meeting of the Association for Computational Linguistics (ACL), pages 589-596, Ann Arbor, MI.
34. Vapnik, Vladimir. 1998. Statistical Learning Theory. Wiley, New York.
35. Xue, Nianwen and Martha Palmer. 2004. Calibrating features for semantic role labeling. In Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 88-94, Barcelona, Spain.
36. Yi, Szu-ting and Martha Palmer. 2005. The integration of syntactic parsing and semantic role labeling. In Proceedings of the Ninth Conference on Computational Natural Language Learning (CoNLL), pages 237-240, Ann Arbor, MI.