Abstract
Mining the semantics of open relations is an important task in open information extraction (Open IE). For this task, the difficulty is that the expressions of a specific semantic in free texts are always not unique. Therefore, it needs us to deeply capture the semantics behind the various expressions. In this paper, we propose an open relation mapping method combining the instances and semantic expansion, which maps the open relation mentions in free texts to the attribute name in knowledge base to find the real semanics of each open relation mentions. Our method effectively mines semantic expansion beyond the text surface of relation mentions. Experimental results show that our method can achieve 74.4% average accuracy for open relation mapping.
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References
Nakashole, N., Weikum, G., Suchanek, F.: Patty: a taxonomy of relational patterns with semantic types. In: Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning, pp. 1135–1145. Association for Computational Linguistics (2012)
Yates, A., Etzioni, O.: Unsupervised resolution of objects and relations on the web. In: Proceedings of NAACL HLT, pp. 121–130 (2007)
Min, B., Shi, S., Grishman, R., Lin, C.Y.: Ensemble semantics for large-scale unsupervised relation extraction. In: Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning, pp. 1027–1037. Association for Computational Linguistics (2012)
Suchanek, F.M., Kasneci, G., Weikum, G.: Yago: A large ontology from wikipedia and wordnet. Web Semantics: Science, Services and Agents on the World Wide Web 6(3), 203–217 (2008)
Zeng, D., Lai, S., Zhang, Y.: Open entity attribute-value extraction from unstructured text. In: Proceedings of the 2012 China Conference on Information Retrieval. Jiangxi Normal University (2012)
Zhao, J., Liu, K., Zhou, G., Cai, L.: Open information extraction. Journal of Chinese Information Processing 25(6), 98–110 (2011)
Yates, A., Cafarella, M., Banko, M., Etzioni, O., Broadhead, M., Soderland, S.: Textrunner: open information extraction on the web. In: Proceedings of Human Language Technologies: The Annual Conference of the North American Chapter of the Association for Computational Linguistics: Demonstrations, pp. 25–26. Association for Computational Linguistics (2007)
Fader, A., Soderland, S., Etzioni, O.: Identifying relations for open information extraction. In: Proceedings of the Conference on Empirical Methods in Natural Language Processing, pp. 1535–1545. Association for Computational Linguistics (2011)
Soderland, S., Roof, B., Qin, B., Xu, S., Etzioni, O., et al.: Adapting open information extraction to domain-specific relations. AI Magazine 31(3), 93–102 (2010)
Soderland, S., Mandhani, B.: Moving from textual relations to ontologized relations. In: Proc. AAAI Spring Symposium on Machine Reading (2007)
Mintz, M., Bills, S., Snow, R., Jurafsky, D.: Distant supervision for relation extraction without labeled data. In: Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP, vol. 2, pp. 1003–1011. Association for Computational Linguistics (2009)
Takamatsu, S., Sato, I., Nakagawa, H.: Reducing wrong labels in distant supervision for relation extraction. In: Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Long Papers, vol. 1, pp. 721–729. Association for Computational Linguistics (2012)
Surdeanu, M., Tibshirani, J., Nallapati, R., Manning, C.D.: Multi-instance multi-label learning for relation extraction. In: EMNLP-CoNLL 2012, pp. 455–465 (2012)
Auer, S., Bizer, C., Kobilarov, G., Lehmann, J., Cyganiak, R., Ives, Z.G.: DBpedia: A nucleus for a web of open data. In: Aberer, K., et al. (eds.) ASWC 2007 and ISWC 2007. LNCS, vol. 4825, pp. 722–735. Springer, Heidelberg (2007)
Kok, S., Domingos, P.: Extracting semantic networks from text via relational clustering. In: Daelemans, W., Goethals, B., Morik, K. (eds.) ECML PKDD 2008, Part I. LNCS (LNAI), vol. 5211, pp. 624–639. Springer, Heidelberg (2008)
Jimenez, S., Becerra, C., Gelbukh, A., Gonzalez, F.: Generalized mongue-elkan method for approximate text string comparison. In: Gelbukh, A. (ed.) CICLing 2009. LNCS, vol. 5449, pp. 559–570. Springer, Heidelberg (2009)
Levenshtein, V.I.: Binary codes capable of correcting deletions, insertions and reversals. Soviet Physics Doklady 10, 707 (1966)
Fellbaum, C.: Wordnet: an electronic lexical database (1998/2010) WordNet is available from, http://www.cogsci.princeton.edu/wn
Jiang, J.J., Conrath, D.W.: Semantic similarity based on corpus statistics and lexical taxonomy. arXiv preprint cmp-lg/9709008 (1997)
Lin, D.: An information-theoretic definition of similarity. In: Proceedings of the 15th International Conference on Machine Learning, San Francisco, vol. 1, pp. 296–304 (1998)
Milne, D.N., Witten, I.H.: Learning to link with wikipedia. In: CIKM 2008, pp. 509–518 (2008)
Strube, M., Ponzetto, S.P.: Wikirelate! computing semantic relatedness using wikipedia. In: AAAI 2006, p. 1 (2006)
Gabrilovich, E., Markovitch, S.: Computing semantic relatedness using wikipedia-based explicit semantic analysis. In: Proceedings of the 20th International Joint Conference on Artificial Intelligence, vol. 6, p. 12 (2007)
Porter, M.F.: An algorithm for suffix stripping. Program: electronic library and information systems 14(3), 130–137 (1980)
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Liu, F., He, S., Liu, S., Zhou, G., Liu, K., Zhao, J. (2013). Open Relation Mapping Based on Instances and Semantics Expansion. In: Banchs, R.E., Silvestri, F., Liu, TY., Zhang, M., Gao, S., Lang, J. (eds) Information Retrieval Technology. AIRS 2013. Lecture Notes in Computer Science, vol 8281. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-45068-6_28
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DOI: https://doi.org/10.1007/978-3-642-45068-6_28
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