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Modelling and Processing Wordnets in OWL

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Modeling, Learning, and Processing of Text Technological Data Structures

Part of the book series: Studies in Computational Intelligence ((SCI,volume 370))

Abstract

In this contribution, we discuss and compare alternative options of modelling the entities and relations of wordnet-like resources in the Web Ontology Language OWL. Based on different modelling options, we developed three models of representing wordnets in OWL, i.e. the instance model, the class model, and the metaclass model. These OWL models mainly differ with respect to the ontological status of lexical units (word senses) and the synsets. While in the instance model lexical units and synsets are represented as individuals, in the class model they are represented as classes; both model types can be encoded in the dialect OWL DL. As a third alternative, we developed a metaclass model in OWL FULL, in which lexical units and synsets are defined as metaclasses, the individuals of which are classes themselves. We apply the three OWL models to each of three wordnet-style resources: (1) a subset of the German wordnet GermaNet, (2) the wordnet-style domain ontology TermNet, and (3) GermaTermNet, in which TermNet technical terms and GermaNet synsets are connected by means of a set of “plug-in” relations. We report on the results of several experiments in which we evaluated the performance of querying and processing these different models: (1) A comparison of all three OWL models (class, instance, and metaclass model) of TermNet in the context of automatic text-to-hypertext conversion, (2) an investigation of the potential of the GermaTermNet resource by the example of a wordnet-based semantic relatedness calculation.

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Author information

Authors and Affiliations

  1. Institut für Deutsche Sprache, Programmbereich Korpuslinguistik, R5, 6-13, D-68161, Mannheim, Germany

    Harald Lüngen

  2. Institute for German Language and Literature, Technische Universität Dortmund, Emil-Figge-Straße 50, D-44221, Dortmund, Germany

    Michael Beißwenger, Bianca Selzam & Angelika Storrer

Authors
  1. Harald Lüngen
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  2. Michael Beißwenger
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  3. Bianca Selzam
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  4. Angelika Storrer
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Editor information

Editors and Affiliations

  1. Faculty of Linguistics and Literature, Bielefeld University, Universitätsstraße 25, 33615, Bielefeld, Germany

    Alexander Mehler

  2. Institute of Cognitive Science, University of Osnabrück, Albrechtstr. 28, 49076, Osnabrück, Germany

    Kai-Uwe Kühnberger

  3. Angewandte Sprachwissenschaft und, Justus-Liebig-Universität Gießen, Computerlinguistik, Otto-Behaghel-Straße 10D, 35394, Gießen, Germany

    Henning Lobin  & Harald Lüngen  & 

  4. Institut für deutsche Sprache und Literatur, Technical University Dortmund, Emil-Figge-Straße 50, 44227, Dortmund, Germany

    Angelika Storrer

  5. SFB 441 Linguistic Data Structures, Eberhard Karls Universität Tübingen, Nauklerstraße 35, 72074, Tübingen, Germany

    Andreas Witt

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Lüngen, H., Beißwenger, M., Selzam, B., Storrer, A. (2011). Modelling and Processing Wordnets in OWL. In: Mehler, A., Kühnberger, KU., Lobin, H., Lüngen, H., Storrer, A., Witt, A. (eds) Modeling, Learning, and Processing of Text Technological Data Structures. Studies in Computational Intelligence, vol 370. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22613-7_17

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  • DOI: https://doi.org/10.1007/978-3-642-22613-7_17

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-22612-0

  • Online ISBN: 978-3-642-22613-7

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