Argument Mining Using Argumentation Scheme Structures

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Abstract

Argumentation schemes are patterns of human reasoning which have been detailed extensively in philosophy and psychology. In this paper we demonstrate that the structure of such schemes can provide rich information to the task of automatically identify complex argumentative structures in natural language text. By training a range of classifiers to identify the individual proposition types which occur in these schemes, it is possible not only to determine where a scheme is being used, but also the roles played by its component parts. Furthermore, this task can be performed on segmented natural language, with no prior knowledge of the text’s argumentative structure.
Original languageEnglish
Title of host publicationComputational Models of Argument
Subtitle of host publicationProceedings from the Sixth International Conference on Computational Models of Argument (COMMA)
EditorsPietro Baroni, Thomas F. Gordon, Tatjana Scheffler, Manfred Stede
Place of PublicationNetherlands
PublisherIOS Press
Pages379-390
Number of pages12
Volume287
ISBN (Electronic)9781614996866
ISBN (Print)9781614996859
DOIs
Publication statusPublished - 2016
EventThe 6th International Conference on Computational Models of Argument - University of Potsdam, Potsdam, Germany
Duration: 13 Sep 201616 Sep 2016
http://www.ling.uni-potsdam.de/comma2016/

Publication series

NameFrontiers in Artificial Intelligence and Applications
PublisherIOS Press
Volume287
ISSN (Print)0922-6389
ISSN (Electronic)1879-8314

Conference

ConferenceThe 6th International Conference on Computational Models of Argument
CountryGermany
CityPotsdam
Period13/09/1616/09/16
Internet address

Keywords

  • Argumentation Schemes
  • Argument Mining
  • Natural Language Processing

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