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An NLP-Based Ontology Population for a Risk Management Generic Structure

Author

Listed:
  • Jawad Makki

    (UT Capitole - Université Toulouse Capitole - UT - Université de Toulouse)

  • Anne-Marie Alquier

    (UT Capitole - Université Toulouse Capitole - UT - Université de Toulouse)

  • Violaine Prince

    (TEXTE - Exploration et exploitation de données textuelles - LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier - UM - Université de Montpellier - CNRS - Centre National de la Recherche Scientifique)

Abstract

In this paper we propose an NLP-based Ontology Population approach for a Generic Structure instantiation from natural language texts, in the domain of Risk Management. The approach is semi-automatic and based on combined NLP techniques using domain expert intervention for control and validation. It relies on the predicative power of verbs in the instantiation process. It is not domain dependent since it heavily relies on linguistic knowledge. We demonstrate the effectiveness of our method on the ontology of the PRIMA project (supported by the European community) and we populate this generic domain ontology via an available corpus. A first validation of the approach is done through an experiment with Chemical Fact Sheets from Environmental Protection Agency.

Suggested Citation

  • Jawad Makki & Anne-Marie Alquier & Violaine Prince, 2008. "An NLP-Based Ontology Population for a Risk Management Generic Structure," Post-Print lirmm-00332138, HAL.
    • Handle: RePEc:hal:journl:lirmm-00332138
    as

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