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International Joint Conference on Knowledge Discovery, Knowledge Engineering, and Knowledge Management

IC3K 2011: Knowledge Discovery, Knowledge Engineering and Knowledge Management pp 141–155Cite as

Using Distant Supervision for Extracting Relations on a Large Scale

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 348))

Abstract

Most of Information Extraction (IE) systems are designed for extracting a restricted number of relations in a specific domain. Recent work about Web-scale knowledge extraction has changed this perspective by introducing large-scale IE systems. Such systems are open-domain and characterized by a large number of relations, which makes traditional approaches such as handcrafting rules or annotating corpora for training statistical classifiers difficult to apply in such context. In this article, we present an IE system based on a weakly supervised method for learning relation patterns. This method extracts without supervision occurrences of relations from a corpus and uses them as examples for learning relation patterns. We also present the results of the application of this system to the data of the 2010 Knowledge Base Population evaluation campaign.

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Author information

Authors and Affiliations

  1. CEA LIST, Vision and Content Engineering Laboratory, Gif-sur-Yvette, F-91191, France

    Ludovic Jean-Louis, Romaric Besançon, Olivier Ferret & Adrien Durand

Authors
  1. Ludovic Jean-Louis
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  2. Romaric Besançon
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  3. Olivier Ferret
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  4. Adrien Durand
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Editor information

Editors and Affiliations

  1. IST - Technical University of Lisbon, Av.Rovisco Pais, 1, 1049-001, Lisbon, Portugal

    Ana Fred

  2. Delft University of Technology, Mekelweg 4, 2628 CD, Delft, The Netherlands

    Jan L. G. Dietz

  3. Informatics Research Centre, Henley Business School, University of Reading, RG6 6UD, Reading, UK

    Kecheng Liu

  4. INSTICC and IPS, Estefanilha, Setúbal, Portugal

    Joaquim Filipe

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Jean-Louis, L., Besançon, R., Ferret, O., Durand, A. (2013). Using Distant Supervision for Extracting Relations on a Large Scale. In: Fred, A., Dietz, J.L.G., Liu, K., Filipe, J. (eds) Knowledge Discovery, Knowledge Engineering and Knowledge Management. IC3K 2011. Communications in Computer and Information Science, vol 348. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37186-8_9

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  • DOI: https://doi.org/10.1007/978-3-642-37186-8_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-37185-1

  • Online ISBN: 978-3-642-37186-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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