Modeling Textual Cohesion for Event Extraction

Proceedings of the 26th AAAI Conference on Artificial Intelligence, AAAI 2012

Volumn , Issue , 2012, Pages 1664-1670

  Huang, Ruihong ^a   Riloff, Ellen ^a  

^a University of Utah   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ADHESION; ARTIFICIAL INTELLIGENCE; EXTRACTION;

BOTTOM UP APPROACH; DOMAIN SPECIFIC; EVENTS EXTRACTIONS; EXTRACTION SYSTEMS; LEXICAL ASSOCIATIONS; NOVEL COMPONENT; PROPERTY; SENTENCE CLASSIFIERS; SPECIFIC DISTRIBUTION; YIELD STATE;

FILLERS;

EID: 85167403109     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (27)

1. Appelt, D.; Hobbs, J.; Bear, J.; Israel, D.; and Tyson, M. 1993. FASTUS: a finite-state processor for information extraction from real-world text. In Proceedings of the Thirteenth International Joint Conference on Artificial Intelligence.
2. Barzilay, R., and Lee, L. 2004. Catching the drift: Probabilistic content models, with applications to generation and summarization. In Proceedings of the Annual Meeting of the North American Chapter of the Association for Computational Linguistics (HLT/NAACL 2004).
3. Chieu, H., and Ng, H. 2002. A Maximum Entropy Approach to Information Extraction from Semi-Structured and Free Text. In Proceedings of the 18th National Conference on Artificial Intelligence.
4. Finkel, J.; Grenager, T.; and Manning, C. 2005. Incorporating Non-local Information into Information Extraction Systems by Gibbs Sampling. In Proceedings of the 43rd Annual Meeting of the Association for Computational Linguistics, 363-370.
5. Finn, A., and Kushmerick, N. 2004. Multi-level Boundary Classification for Information Extraction. In Proceedings of the 15th European Conference on Machine Learning, 111-122.
6. Gu, Z., and Cercone, N. 2006. Segment-Based Hidden Markov Models for Information Extraction. In Proceedings of the 21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics, 481-488.
7. Huang, R., and Riloff, E. 2011. Peeling Back the Layers: Detecting Event Role Fillers in Secondary Contexts. In Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies (ACL-11).
8. Ji, H., and Grishman, R. 2008. Refining Event Extraction through Cross-Document Inference. In Proceedings of ACL-08: HLT, 254-262.
9. Lafferty, J.; McCallum, A.; and Pereira, F. 2001. Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data. In Proceedings of the Eighteenth International Conference on Machine Learning.
10. Li, Y.; Bontcheva, K.; and Cunningham, H. 2005. Using Uneven Margins SVM and Perceptron for Information Extraction. In Proceedings of Ninth Conference on Computational Natural Language Learning, 72-79.
11. Liao, S., and Grishman, R. 2010. Using Document Level Cross-Event Inference to Improve Event Extraction. In Proceedings of the 48st Annual Meeting on Association for Computational Linguistics (ACL-10).
12. Lin, Z.; Ng, H. T.; and Kan, M.-Y. 2010. A PDTB-Styled End-to-End Discourse Parser. In Technical Report TRB8/10, National University of Singapore, August.
13. Marneffe, M.-C. d.; MacCartney, B.; and Manning, C. D. 2006. Generating Typed Dependency Parses from Phrase Structure Parses. In Proceedings of the Fifth Conference on Language Resources and Evaluation (LREC-2006).
14. Maslennikov, M., and Chua, T. 2007. A Multi-Resolution Framework for Information Extraction from Free Text. In Proceedings of the 45th Annual Meeting of the Association for Computational Linguistics.
15. MUC-4 Proceedings. 1992. Proceedings of the Fourth Message Understanding Conference (MUC-4). Morgan Kaufmann.
16. Patwardhan, S., and Riloff, E. 2007. Effective Information Extraction with Semantic Affinity Patterns and Relevant Regions. In Proceedings of 2007 the Conference on Empirical Methods in Natural Language Processing (EMNLP-2007).
17. Patwardhan, S., and Riloff, E. 2009. A Unified Model of Phrasal and Sentential Evidence for Information Extraction. In Proceedings of 2009 the Conference on Empirical Methods in Natural Language Processing (EMNLP-2009).
18. Porter, M. 1980. An algorithm for suffix stripping. Program 14(3):130-137.
19. Prasad, R.; Dinesh, N.; A., L.; Miltsakaki, E.; Robaldo, L.; A., J.; and Webber, B. 2008. The Penn Discourse Treebank 2.0. In Proceedings of the Sixth Conference on Language Resources and Evaluation (LREC-2008).
20. Rabiner, L. 1989. A tutorial on hidden Markov models and selected applications in speech recognition. Proceedings of the IEEE 77(2):257-286.
21. Riloff, E., and Phillips, W. 2004. An Introduction to the Sundance and AutoSlog Systems. Technical Report UUCS-04-015, School of Computing, University of Utah.
22. Riloff, E. 1993. Automatically Constructing a Dictionary for Information Extraction Tasks. In Proceedings of the 11th National Conference on Artificial Intelligence.
23. Sauper, C.; Haghighi, A.; and Barzilay, R. 2010. Incorporating Content Structure into Text Analysis Applications. In Proceedings of 2010 the Conference on Empirical Methods in Natural Language Processing (EMNLP-2010).
24. Soderland, S.; Fisher, D.; Aseltine, J.; and Lehnert, W. 1995. CRYSTAL: Inducing a conceptual dictionary. In Proc. of the Fourteenth International Joint Conference on Artificial Intelligence, 1314-1319.
25. Soricut, R., and Marcu, D. 2006. Discourse Generation Using Utility-Trained Coherence Models. In Proceedings of Joint Conference of the International Committee on Computational Linguistics and the Association for Computational Linguistics (COLING/ACL-06), 803-810.
26. Sudo, K.; Sekine, S.; and Grishman, R. 2003. An Improved Extraction Pattern Representation Model for Automatic IE Pattern Acquisition. In Proceedings of the 41st Annual Meeting of the Association for Computational Linguistics (ACL-03).
27. Yu, K.; Guan, G.; and Zhou, M. 2005. Resumé Information Extraction with Cascaded Hybrid Model. In Proceedings of the 43rd Annual Meeting of the Association for Computational Linguistics, 499-506.