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Enhancing Multilingual Biomedical Terminologies via Machine Translation from Parallel Corpora

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Book cover Natural Language Processing and Information Systems (NLDB 2014)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8455))

Abstract

Creating and maintaining terminologies by human experts is known to be a resource-expensive task. We here report on efforts to computationally support this process by treating term acquisition as a machine translation-guided classification problem capitalizing on parallel multilingual corpora. Experiments are described for French, German, Spanish and Dutch parts of a multilingual biomedical terminology, for which we generated 18k, 23k, 19k and 12k new terms and synonyms, respectively; about one half relate to concepts that have not been lexically labeled before. Based on expert assessment of a sample of the novel German segment about 80% of these newly acquired terms were judged as linguistically correct and bio-medically reasonable additions to the terminology.

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Authors and Affiliations

  1. Jena University Language & Information Engineering (Julie) Lab, Friedrich-Schiller-Universität Jena, Jena, Germany

    Johannes Hellrich & Udo Hahn

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  1. Johannes Hellrich
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  2. Udo Hahn
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Editors and Affiliations

  1. Conservatoire National des Arts et Métiers, Computer Science,, 2 rue Conté, 75003, Paris, France

    Elisabeth Métais

  2. Cirad, TETIS, 500 rue J.F. Breton, 34093, Montpellier Cedex 5, France

    Mathieu Roche

  3. Irstea, TETIS, 500 rue J.F. Breton, 34093, Montpellier Cedex 5, France

    Maguelonne Teisseire

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Hellrich, J., Hahn, U. (2014). Enhancing Multilingual Biomedical Terminologies via Machine Translation from Parallel Corpora. In: Métais, E., Roche, M., Teisseire, M. (eds) Natural Language Processing and Information Systems. NLDB 2014. Lecture Notes in Computer Science, vol 8455. Springer, Cham. https://doi.org/10.1007/978-3-319-07983-7_2

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  • DOI: https://doi.org/10.1007/978-3-319-07983-7_2

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-07982-0

  • Online ISBN: 978-3-319-07983-7

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