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Information Extraction

In: Handbook on Ontologies

Author

Listed:
  • Claire Nédellec

    (INRA)

  • Adeline Nazarenko

    (Université Paris-Nord)

  • Robert Bossy

    (INRA)

Abstract

Summary Information Extraction (IE) addresses the intelligent access to document contents by automatically extracting information relevant to a given task. This chapter focuses on how ontologies can be exploited to interpret the textual document content for IE purposes. It makes a state of the art of IE systems from the point of view of IE as a knowledge-based NLP process. It reviews the different steps of NLP necessary for IE tasks: named entity recognition, term analysis, semantic typing and identification specific relations. It stresses on the importance of ontological knowledge for performing each step and presents corpus-based methods for the acquisition of the required knowlege. This chapter shows that IE is an ontology-based activity and argues that future effort in IE should focus on formalizing and reinforcing the relation between the text extraction and the ontology model. The discussion gives authors’ insights on the integration of ontological knowledge in IE systems from a formal and pragmatic point of view. Examples in this chapter are taken from IE tasks for biology since this domain attracts a large community of IE specialists and provides a large number of ontological resources.

Suggested Citation

  • Claire Nédellec & Adeline Nazarenko & Robert Bossy, 2009. "Information Extraction," International Handbooks on Information Systems, in: Steffen Staab & Rudi Studer (ed.), Handbook on Ontologies, pages 663-685, Springer.
    • Handle: RePEc:spr:ihichp:978-3-540-92673-3_30
    DOI: 10.1007/978-3-540-92673-3_30
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