Abstract
The volume of published data in the Web has been increasing, and a great amount of those data is available in a natural language format. Manually analyzing each document is a time-consuming and tedious task. Thus, Open IE area emerges to help the extraction of semantic relationships in a large number of texts written in a natural language from different domains. Although a semantic analysis does not guarantee complete accuracy in extracting relations, a pragmatic analysis becomes important on Open EI to identify additional meanings (unsaid) that goes beyond semantics in a text. Our work developed a method for Open Information Extraction to extract relations from texts written in Portuguese in a first pragmatic level. We stated that a first pragmatic level deals with inferential, contextual and intentional aspects. We evaluate our approach, and our results outstand the most relevant related work on comparing accuracy and minimality measures.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
Notes
- 1.
Available: https://pt.wikipedia.org/. Accessed: 08/05/2018.
- 2.
Available: http://www.linguateca.pt/cetenfolha/. Accessed: 08/05/2018.
References
Banko, M., Cafarella, M.J., Soderland, S., Broadhead, M., Etzioni, O.: Open information extraction for the web. IJCAI 7, 2670–2676 (2007)
Banko, M., Etzioni, O., Center, T.: The tradeoffs between open and traditional relation extraction. In: ACL, vol. 8, pp. 28–36. Association for Computational Linguistics, Stroudsburg (2008)
Bast, H., Haussmann, E.: Open information extraction via contextual sentence decomposition. In: 2013 IEEE Seventh International Conference on Semantic Computing (ICSC), ICSC 2013, pp. 154–159. IEEE, Irvine (2013)
Bast, H., Haussmann, E.: More informative open information extraction via simple inference. In: de Rijke, M., Kenter, T., de Vries, A.P., Zhai, C.X., de Jong, F., Radinsky, K., Hofmann, K. (eds.) ECIR 2014. LNCS, vol. 8416, pp. 585–590. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-06028-6_61
Carletta, J.: Assessing agreement on classification tasks: the kappa statistic. Comput. Linguist. 22(2), 249–254 (1996). http://dl.acm.org/citation.cfm?id=230386.230390
da Costa, J.C.: A teoria inferencial das implicaturas: descrição do modelo clássico de grice. Letras de Hoje 44(3) (2009)
Del Corro, L., Gemulla, R.: Clausie: Clause-based open information extraction. In: Proceedings of the 22nd International Conference on World Wide Web, WWW 2013, pp. 355–366. ACM, New York (2013). https://doi.org/10.1145/2488388.2488420
Fader, A., Soderland, S., Etzioni, O.: Identifying relations for open information extraction. In: Proceedings of the Conference on Empirical Methods in Natural Language Processing, EMNLP 2011, pp. 1535–1545. Association for Computational Linguistics, Stroudsburg (2011). http://dl.acm.org/citation.cfm?id=2145432.2145596
Gamallo, P., Garcia, M.: Multilingual open information extraction. In: Pereira, F., Machado, P., Costa, E., Cardoso, A. (eds.) EPIA 2015. LNCS (LNAI), vol. 9273, pp. 711–722. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-23485-4_72
Grice, H.P.: Studies in the Way of Words. Harvard University Press (1989)
Mausam, M.S., Bart, R., Soderland, S., Etzioni, O.: Open language learning for information extraction. In: Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning, EMNLP-CoNLL 2012, pp. 523–534. Association for Computational Linguistics, Stroudsburg (2012). http://dl.acm.org/citation.cfm?id=2390948.2391009
de Oliveira, L.S., Glauber, R., Claro, D.B.: Dependentie: an open information extraction system on portuguese by a dependence analysis. Encontro Nacional de Inteligência Artificial e Computacional (2017)
Sena, C.F.L., Glauber, R., Claro, D.B.: Inference approach to enhance a portuguese open information extraction. In: Proceedings of the 19th International Conference on Enterprise Information Systems, ICEIS, vol. 1, pp. 442–451. INSTICC, ScitePress, Porto, Portugal (2017). https://doi.org/10.5220/0006338204420451
Wu, F., Weld, D.S.: Open information extraction using wikipedia. In: Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics, ACL 2010, pp. 118–127. Association for Computational Linguistics, Stroudsburg (2010). http://dl.acm.org/citation.cfm?id=1858681.1858694
Acknowledgement
Authors would like to thank FAPESB BOL3288/2015 for finantial support.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Switzerland AG
About this paper
Cite this paper
Sena, C.F.L., Claro, D.B. (2018). Pragmatic Information Extraction in Brazilian Portuguese Documents. In: Villavicencio, A., et al. Computational Processing of the Portuguese Language. PROPOR 2018. Lecture Notes in Computer Science(), vol 11122. Springer, Cham. https://doi.org/10.1007/978-3-319-99722-3_5
Download citation
DOI: https://doi.org/10.1007/978-3-319-99722-3_5
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-99721-6
Online ISBN: 978-3-319-99722-3
eBook Packages: Computer ScienceComputer Science (R0)