Improvement of n-ary relation extraction by adding lexical semantics to distant-supervision rule learning

ICAART 2015 - 7th International Conference on Agents and Artificial Intelligence, Proceedings

Volumn 2, Issue , 2015, Pages 317-324

  Li, Hong ^a   Krause, Sebastian ^a   Xu, Feiyu ^a   Moro, Andrea ^b   Uszkoreit, Hans ^a   Navigli, Roberto ^b  

^a GERMAN RESEARCH CENTER FOR ARTIFICIAL INTELLIGENCE DFKI   (Germany)

^b SAPIENZA UNIVERSITY OF ROME   (Italy)

Author keywords

Lexical semantics; Pattern extraction; Relation extraction

Indexed keywords

ARTIFICIAL INTELLIGENCE; EXTRACTION;

BASELINE SYSTEMS; EXPLICIT SEMANTICS; LEXICAL SEMANTICS; PATTERN EXTRACTION; RECALL AND PRECISION; RELATION EXTRACTION; RULE LEARNING; SHORTEST PATH;

SEMANTICS;

EID: 84943270444     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.5220/0005187303170324     Document Type: Conference Paper

References (32)

1. Agichtein, E. (2006). Confidence estimation methods for partially supervised information extraction. In Proc. of the Sixth SIAM International Conference on Data Mining.
2. Alfonseca, E., Filippova, K., Delort, J.-Y., and Garrido, G. (2012). Pattern learning for relation extraction with a hierarchical topic model. In Proc. of ACL (2), pages 54-59.
3. Appelt, D. E. and Israel, D. J. (1999). Introduction to information extraction technology. A tutorial prepared for IJCAI-99.
4. Banko, M. and Etzioni, O. (2008). The Tradeoffs Between Open and Traditional Relation Extraction. In Proc. of ACL/HLT, pages 28-36.
5. Bollacker, K. D., Evans, C., Paritosh, P., Sturge, T., and Taylor, J. (2008). Freebase: a collaboratively created graph database for structuring human knowledge. In Proc. of SIGMOD, pages 1247-1250.
6. Bond, F. and Kyonghee, P. (2012). A survey of wordnets and their licenses. In Proceedings of the 6th International Global WordNet Conference, pages 64-71.
7. Bunescu, R. C. and Mooney, R. J. (2005). A Shortest Path Dependency Kernel for Relation Extraction. In Proc. of HLT, pages 724-731.
8. Chowdhury, M. F. M. and Lavelli, A. (2012). Combining tree structures, flat features and patterns for biomedical relation extraction. In Proceedings of the 13th Conference of the European Chapter of the Association for Computational Linguistics, EACL'12, pages 420-429, Stroudsburg, PA, USA. Association for Computational Linguistics.
9. Etzioni, O., Fader, A., Christensen, J., Soderland, S., and Mausam (2011). Open Information Extraction: The Second Generation. In Proc. of IJCAI, page 310.
10. Fader, A., Soderland, S., and Etzioni, O. (2011). Identifying Relations for Open Information Extraction. In Proc. of EMNLP, page 15351545.
11. Fellbaum, C. (1998). WordNet: An Electronic Lexical Database. MIT Press.
12. Grishman, R. and Sundheim, B. (1996). Message understanding conference - 6: A brief history. In Proc. of the 16th International Conference on Computational Linguistics, Copenhagen.
13. Grishman, R., Westbrook, D., and Meyers, A. (2005). Nyu's english ace 2005 system description. Technical report, Proteus Project, Department of Computer Science, New York University.
14. Jean-Louis, L., Besanon, R., Ferret, O., and Durand, A. (2013). Using Distant Supervision for Extracting Relations on a Large Scale. In Fred, A., Dietz, J., Liu, K., and Filipe, J., editors, Knowledge Discovery, Knowledge Engineering and Knowledge Management, volume 348 of Communications in Computer and Information Science, page 141155. Springer Berlin Heidelberg.
15. Krause, S., Li, H., Uszkoreit, H., and Xu, F. (2012). Largescale learning of relation-extraction rules with distant supervision from the web. In Proc. of 11th ISWC, Part I, pages 263-278.
16. Li, H., Krause, S., Xu, F., Uszkoreit, H., Hummel, R., and Mironova, V. (2014). Annotating relation mentions in tabloid press. In Proceedings of the 9th edition of the Language Resources and Evaluation Conference.
17. Mausam, Schmitz, M., Soderland, S., Bart, R., and Etzioni, O. (2012). Open Language Learning for Information Extraction. In Proc. of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning, pages 523-534, Jeju Island, Korea. Association for Computational Linguistics.
18. Min, B., Grishman, R., Wan, L., Wang, C., and Gondek, D. (2013). Distant supervision for relation extraction with an incomplete knowledge base. In Proceedings of NAACL-HLT, pages 777-782.
19. Mintz, M., Bills, S., Snow, R., and Jurafsky, D. (2009). Distant supervision for relation extraction without labeled data. In Proc. of ACL/AFNLP, page 10031011.
20. Moro, A., Li, H., Krause, S., Xu, F., Navigli, R., and Uszkoreit, H. (2013). Semantic rule filtering for web-scale relation extraction. In International Semantic Web Conference (1), pages 347-362.
21. Moro, A. and Navigli, R. (2013). Integrating syntactic and semantic analysis into the open information extraction paradigm. In Proc. of IJCAI, pages 2148-2154.
22. Moro, A., Raganato, A., and Navigli, R. (2014). Entity linking meets word sense disambiguation: A unified approach. Transactions of the Association for Computational Linguistics, 2:231-244.
23. Navigli, R. (2009). Word Sense Disambiguation: A survey. ACM Comput. Surv., 41(2):1-69.
24. Navigli, R. and Ponzetto, S. P. (2012). BabelNet: The automatic construction, evaluation and application of a wide-coverage multilingual semantic network. Artificial Intelligence, 193:217-250.
25. Nivre, J., Hall, J., Nilsson, J., Chanev, A., Eryigit, G., Kübler, S., Marinov, S., and Marsi, E. (2007). Maltparser: A language-independent system for data-driven dependency parsing. Natural Language Engineering, 13(2):95-135.
26. Ravichandran, D. and Hovy, E. H. (2002). Learning surface text patterns for a Question Answering System. In Proc. of ACL, pages 41-47.
27. Wu, F. and Weld, D. S. (2010). Open information extraction using wikipedia. In Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics, pages 118-127. Association for Computational Linguistics.
28. Xu, F., Uszkoreit, H., and Li, H. (2007). A seed-driven bottom-up machine learning framework for extracting relations of various complexity. In Proc. of ACL.
29. Xu, H., Hu, C., and Shen, G. (2009). Discovery of dependency tree patterns for relation extraction. In PACLIC, pages 851-858.
30. Xu, Y., Kim, M.-Y., Quinn, K., Goebel, R., and Barbosa, D. (2013). Open Information Extraction with Tree Kernels. In Proc. of NAACL-HLT, pages 868-877, Atlanta, Georgia. Association for Computational Linguistics.
31. Yangarber, R., Grishman, R., and Tapanainen, P. (2000). Automatic acquisition of domain knowledge for information extraction. In Proc. of COLING, pages 940-946.
32. Zelenko, D., Aone, C., and Richardella, A. (2003). Kernel methods for relation extraction. The Journal of Machine Learning Research, 3:1083-1106.