Minority vote: At-least-N voting improves recall for extracting relations

COLING/ACL 2006 - 21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Main Conference Poster Sessions

Volumn , Issue , 2006, Pages 460-466

  Kambhatla, Nanda ^a  

^a IBM T J WATSON RESEARCH CENTER   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CLASS LABELS; COREFERENCE; HIGH-PRECISION; NAMED ENTITIES; RELATION EXTRACTION;

EID: 85119972733     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (18)

1. D. M. Bikel, S. Miller, R. Schwartz, and R. Weischedel. 1997. Nymble: a high-performance learning name-finder. In Proceedings of ANLP-97, pages 194-201.
2. A. Borthwick. 1999. A Maximum Entropy Approach to Named Entity Recognition. Ph.D. thesis, New York University.
3. L. Breiman. 1996. Bagging predictors. In Machine Learning, volume 24, page 123.
4. E. Brill and J. Wu. 1998. Classifier combination for improved lexical disambiguation. Proceedings of COLING-ACL'98, pages 191-195, August.
5. Radu Florian and David Yarowsky. 2002. Modeling consensus: Classifier combination for word sense disambiguation. In Proceedings of EMNLP'02, pages 25-32.
6. R. Florian, A. Ittycheriah, H. Jing, and T. Zhang. 2003. Named entity recognition through classifier combination. In Proceedings of CoNNL'03, pages 168-171.
7. R. Florian, H. Hassan, A. Ittycheriah, H. Jing, N. Kambhatla, X. Luo, N Nicolov, and S Roukos. 2004. A statistical model for multilingual entity detection and tracking. In Proceedings of the Human Language Technology Conference of the North American Chapter of the Association for Computational Linguistics: HLT-NAACL 2004, pages 1-8.
8. J. Henderson and E. Brill. 1999. Exploiting diversity in natural language processing: Combining parsers. In Proceedings on EMNLP99, pages 187-194.
9. T. K. Ho, J. J. Hull, and S. N. Srihari. 1994. Decision combination in multiple classifier systems. IEEE Transactions on Pattern Analysis and Machine Intelligence, 16(1):66-75, January.
10. Nanda Kambhatla. 2004. Combining lexical, syntactic, and semantic features with maximum entropy models for information extraction. In The Proceedings of 42st Annual Meeting of the Association for Computational Linguistics, pages 178-181, Barcelona, Spain, July. Association for Computational Linguistics.
11. D. Magerman. 1993. Parsing as statistical pattern recognition.
12. NIST. 2004. The ACE evaluation plan. www.nist.gov/speech/tests/ace/index.htm.
13. Adwait Ratnaparkhi. 1999. Learning to parse natural language with maximum entropy models. Machine Learning, 34:151-178.
14. W. M. Soon, H. T. Ng, and C. Y. Lim. 2001. A machine learning approach to coreference resolution of noun phrases. Computational Linguistics, 27(4):521-544.
15. E. F. Tjong Kim Sang, W. Daelemans, H. Dejean, R. Koeling, Y. Krymolowsky, V. Punyakanok, and D. Roth. 2000. Applying system combination to base noun phrase identification. In Proceedings of COLING 2000, pages 857-863.
16. H. van Halteren, J. Zavrel, and W. Daelemans. 1998. Improving data driven wordclass tagging by system combination. In Proceedings of COLING-ACL'98, pages 491-497.
17. L. Xu, A. Krzyzak, and C. Suen. 1992. Methods of combining multiple classifiers and their applications to handwriting recognition. IEEE Trans. on Systems, Man. Cybernet, 22(3):418-435.
18. T. Zhang, F. Damerau, and D. E. Johnson. 2002. Text chunking based on a generalization of Winnow. Journal of Machine Learning Research, 2:615-637.