Abstract
Relation Extraction is the task of identifying and classifying the semantic relations between entities in text. This task is one of the main challenges in Natural Language Processing. In this work, the relation extraction task is treated as sequence labelling problem. We analysed the impact of different representation schemes for the relation descriptors. In particular, we analysed the BIO and IO schemes performance considering a Conditional Random Fields classifier for the extraction of any relation descriptor occurring between named entities in the Organisation domain (Person, Organisation, Place). Overall, the classifier proposed here presents the best results using the IO notation.
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References
Abreu, S.C., Bonamigo, T.L., Vieira, R.: A review on relation extraction with an eye on portuguese. Journal of the Brazilian Computer Society, 1–19 (2013)
Banko, M., Etzioni, O.: The tradeoffs between open and traditional relation extraction. In: McKeown, K., Moore, J.D., Teufel, S., Allan, J., Furui, S. (eds.) ACL, pp. 28–36. The Association for Computer Linguistics (2008)
Batista, D.S., Forte, D., Silva, R., Martins, B., Silva, M.: Extracção de relações semânticas de textos em português explorando a DBpédia e a Wikipédia. Linguamatica 5(1), 41–57 (2013)
Bellare, K., Mccallum, A.: Learning extractors from unlabeled text using relevant databases. In: Sixth International Workshop on Information Integration on the Web (IIWeb) (2007)
Bick, E.: The Parsing System Palavras. Automatic Grammatical Analysis of Portuguese in a Constraint Grammar Framework. University of Arhus (2000)
Brucksen, M., Souza, J.G.C., Vieira, R., Rigo, S.: Sistema serelep para o reconhecimento de relações entre entidades mencionadas. In: Mota, C., Santos, D. (eds.) Segundo HAREM, chap. 14, pp. 247–260. Linguateca (2008)
Cardoso, N.: Rembrandt - reconhecimento de entidades mencionadas baseado em relações e análise detalhada do texto. In: Mota, C., Santos, D. (eds.) Segundo HAREM, chap. 11, pp. 195–211. Linguateca (2008)
Chaves, M.S.: Geo-ontologias e padrões para reconhecimento de locais e de suas relações em textos: o sei-geo no segundo harem. In: Mota, C., Santos, D. (eds.) Segundo HAREM, chap. 13, pp. 231–245. Linguateca (2008)
Chen, Y., Zheng, Q., Wang, W., Chen, Y.: Knowledge element relation extraction using conditional random fields. In: CSCWD, pp. 245–250 (2010)
Collovini, S., Pugens, L., Vanin, A.A., Vieira, R.: Extraction of relation descriptors for Portuguese using conditional random fields. In: Bazzan, A.L.C., Pichara, K. (eds.) IBERAMIA 2014. LNCS, vol. 8864, pp. 108–119. Springer, Heidelberg (2014)
Culotta, A., McCallum, A., Betz, J.: Integrating probabilistic extraction models and data mining to discover relations and patterns in text. In: Proceedings of the Main Conference on HLT-NAACL, HLT-NAACL ’06, pp. 296–303. Association for Computational Linguistics, Stroudsburg (2006)
Finkel, J.R., Grenager, T., Manning, C.: Incorporating non-local information into information extraction systems by gibbs sampling. In: Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics, ACL ’05, pp. 363–370. Association for Computational Linguistics, Stroudsburg (2005)
Jurafsky, D., Martin, J.H.: Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics and Speech Recognition. Prentice Hall Series in Artificial Intelligence, 2nd edn. Pearson Education Ltd., London (2009)
Lafferty, J.D., McCallum, A., Pereira, F.C.N.: Conditional random fields: probabilistic models for segmenting and labeling sequence data. In: Proceedings of the Eighteenth International Conference on Machine Learning, ICML ’01, pp. 282–289. Morgan Kaufmann Publishers Inc., San Francisco (2001)
Li, Y., Jiang, J., Chieu, H.L., Chai, K.M.A.: Extracting relation descriptors with conditional random fields. In: Proceedings of 5th International Joint Conference on Natural Language Processing, pp. 392–400. Asian Federation of Natural Language Processing, Chiang Mai (2011)
McCallum, A., Li, W.: Early results for named entity recognition with conditional random fields, feature induction and web-enhanced lexicons. In: Proceedings of the Seventh Conference on Natural Language Learning at HLT-NAACL 2003, CONLL ’03, vol. 4, pp. 188–191. Association for Computational Linguistics, Stroudsburg (2003)
Ramshaw, L.A., Marcus, M.P.: Text chunking using transformation-based learning. In: Proceedings of the 3rd ACL Workshop on Very Large Corpora, pp. 82–94, Cambridge MA, USA (1995)
Ratinov, L., Roth, D.: Design challenges and misconceptions in named entity recognition. In: Proceedings of the Thirteenth Conference on Computational Natural Language Learning, CoNLL ’09, pp. 147–155. Association for Computational Linguistics, Stroudsburg (2009)
Žitnik, S., Šubelj, L., Lavbič, D., Zrnec, A., Bajec, M.: Collective information extraction using first-order probabilistic models. In: Proceedings of the Fifth Balkan Conference in Informatics, BCI ’12, pp. 279–282. ACM, New York (2012)
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Collovini, S., de Bairros P. Filho, M., Vieira, R. (2015). Analysing the Role of Representation Choices in Portuguese Relation Extraction. In: Mothe, J., et al. Experimental IR Meets Multilinguality, Multimodality, and Interaction. CLEF 2015. Lecture Notes in Computer Science(), vol 9283. Springer, Cham. https://doi.org/10.1007/978-3-319-24027-5_9
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DOI: https://doi.org/10.1007/978-3-319-24027-5_9
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