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Processing Text-Technological Resources in Discourse Parsing

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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))

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Abstract

Discourse parsing of complex text types such as scientific research articles requires the analysis of an input document on linguistic and structural levels that go beyond traditionally employed lexical discourse markers. This chapter describes a text-technological approach to discourse parsing. Discourse parsing with the aim of providing a discourse structure is seen as the addition of a new annotation layer for input documents marked up on several linguistic annotation levels. The discourse parser generates discourse structures according to the Rhetorical Structure Theory. An overview of the knowledge sources and components for parsing scientific journal articles is given. The parser’s core consists of cascaded applications of the GAP, a Generic Annotation Parser. Details of the chart parsing algorithm are provided, as well as a short evaluation in terms of comparisons with reference annotations from our corpus and with recently developed systems with a similar task.

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Author information

Authors and Affiliations

  1. Applied and Computational Linguistics, Justus-Liebig-Universität Gießen, Otto-Behaghel-Straße 10D, D-35394, Gießen, Germany

    Henning Lobin, Harald Lüngen, Mirco Hilbert & Maja Bärenfänger

Authors
  1. Henning Lobin
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  2. Harald Lüngen
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  3. Mirco Hilbert
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  4. Maja Bärenfänger
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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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Lobin, H., Lüngen, H., Hilbert, M., Bärenfänger, M. (2011). Processing Text-Technological Resources in Discourse Parsing. 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_3

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  • DOI: https://doi.org/10.1007/978-3-642-22613-7_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-22612-0

  • Online ISBN: 978-3-642-22613-7

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