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European Conference on Symbolic and Quantitative Approaches to Reasoning and Uncertainty

ECSQARU 2015: Symbolic and Quantitative Approaches to Reasoning with Uncertainty pp 60-71 | Cite as

Representing and Reasoning About Arguments Mined from Texts and Dialogues

  • Leila AmgoudEmail author
  • Philippe Besnard
  • Anthony Hunter
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9161)

Abstract

This paper presents a target language for representing arguments mined from natural language. The key features are the connection between possible reasons and possible claims and recursive embedding of such connections. Given a base of these arguments and counterarguments mined from texts or dialogues, we want be able combine them, deconstruct them, and to analyse them (for instance to check whether the set is inconsistent). To address these needs, we propose a formal language for representing reasons and claims, and a framework for inferencing with the arguments and counterarguments in this formal language.

Keywords

Natural Language Logical Consequence Inference Rule Target Language Sentiment Analysis 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Leila Amgoud
    • 1
    Email author
  • Philippe Besnard
    • 1
  • Anthony Hunter
    • 2
  1. 1.CNRS, IRITUniversité de ToulouseToulouseFrance
  2. 2.University College LondonLondonUK

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