Abstract
One of the growing needs of information extraction (IE) from text is that the IE system must be able to perform enriched inferences in order to discover and extract information. We argue that one reason for the current limitation of the approaches that use semantics for that is that they are based on ontologies that express the characteristics of things represented by names, and seek to draw inferences and to extract information based on such characteristics, disregarding the linguistic praxis (i.e. the uses of the natural language). In this paper, we describe a generic architecture for IE systems based on Semantic Inferentialism. We propose a model that seeks to express the inferential power of concepts and how these concepts, combined in sentence structures, contribute to the inferential power of sentences. We demonstrate the validity of the approach and evaluate it by deploying an application for extracting information about crime reported in on line newspapers.
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References
Grishman, R.: Information Extraction: Techniques and Challenges. In: SCIE 1997: International Summer School on Information Extraction, pp. 10–27. Springer, Heidelberg (1997)
Vieira, R., Lima, V.L.S.: Lingüística Computacional: Princípios e Aplicações. Anais do XXI Congresso da SBC. I Jornada de Atualização em Inteligência Artificial 3, 47–86 (2001)
Dummett, M.: Truth and Other Enigmas. Duckworth, London (1978)
Brandom, R.B.: Articulating Reasons. In: An Introduction to Inferentialism. Harvard University Press, Cambridge (2000)
Lieberman, H., Paternó, F., Klann, M., Wulf, V.: End-User Development: an Emergin Paradigm. End User Development. Cap.1 (2005)
Pinheiro, V., Pequeno, T., Furtado, V., Assunção, T., Freitas, E.: SIM: Um Modelo Semântico-Inferencialista para Sistemas de Linguagem Natural. In: VI Workshop em Tecnologia da Informação e da Linguagem Humana (TIL 2008). WebMedia, Brasil (2008)
Liu, H., Singh, P.: ConceptNet: A Practical Commonsense Reasoning Toolkit. BT Technology Journal 22(4) (2004)
Gentzen, G.: Untersuchungen über das logische Schliessen. Mathematische Zeitschrift 39, 176–210, 405–431 (1935); Szabo, M.: Translated as Investigations into Logical Deduction,and printed. In: The Collected Papers of Gerhard Gentzen, pp. 68–131. North-Holland, Amsterdam (1969)
Prawitz, D.: Natural Deduction: A Proof Theoretical Study. Almqvist & Wiksell, Stockholm (1965)
Bick, E.: The Parsing System “Palavras”. In: Automatic Grammatical Analysis of Portuguese in a Constraint Grammar Framework. Aarhus University Press (2000)
Borges, K., Laender, A.H.F., Medeiros, C., Davis Jr, C.A.: Discovering geographic locations in web pages using urban addresses. In: Proceedings of the 4th ACM workshop on Geographical Information Retrieval (GIR 2007), Lisboa, Portugal, pp. 31–36 (2007)
Cohen, K., Hunter, L.: Getting started in text mining. PLoS Compt Biology 4(1) (2008)
Hobbs, J., Appelt, D., Bear, J., Israel, D., Kameyama, M., Stickel, M., Tyson, M.F.: Fastus: A cascaded finite-state transducer for extracting information from natural-language text. In: Roche, E., Schabes, Y. (eds.) Finite-State Devices for Natural Language Processing, pp. 383–406. MIT Press, Cambridge (1997)
Glickman, O., Jones, R.: Examining machine learning for adaptable end-to-end information extraction systems. In: AAAI 1999 Workshop on Machine Learning for Information Extraction (1999)
Borkar, V., Deshmukh, K., Sarawagi, S.: Automatic segmentation of text into structured records. In: Proceedings of the 2001 ACM SIGMOD International Conference on Management of Data, California, pp. 175–186 (2001)
Geng, J., Yang, J.: AUTOBIB: Automatic extraction and integration of bibliographic information on the web. In: 29th VLDB Conference, Berlin, Germany (2003)
Fellbaum, C. (ed.): WordNet: An electronic lexical database. MIT Press, Cambridge (1998)
Baker, C.F., Fillmore, C.J., Lowe, J.B.: The Berkeley FrameNet Project. In: Proceedings of COLING-ACL (1998)
Kaisser, M., Webber, B.: Question Answering based on Semantic Roles. In: ACL 2007 Workshop on Deep Linguistic Processing (2007)
Saias, J., Quaresma, P.: A proposal for an ontology supported news reader and question-answer system. In: Proceedings of the 2nd Workshop on Ontologies and their Applications (2006)
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Pinheiro, V., Pequeno, T., Furtado, V., Nogueira, D. (2009). Information Extraction from Text Based on Semantic Inferentialism. In: Andreasen, T., Yager, R.R., Bulskov, H., Christiansen, H., Larsen, H.L. (eds) Flexible Query Answering Systems. FQAS 2009. Lecture Notes in Computer Science(), vol 5822. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04957-6_29
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DOI: https://doi.org/10.1007/978-3-642-04957-6_29
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