Classifying arguments by scheme

  • Authors:
  • Vanessa Wei Feng;Graeme Hirst

  • Affiliations:
  • University of Toronto, Toronto, ON, Canada;University of Toronto, Toronto, ON, Canada

  • Venue:
  • HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
  • Year:
  • 2011

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Abstract

Argumentation schemes are structures or templates for various kinds of arguments. Given the text of an argument with premises and conclusion identified, we classify it as an instance of one of five common schemes, using features specific to each scheme. We achieve accuracies of 63--91% in one-against-others classification and 80--94% in pairwise classification (baseline = 50% in both cases).