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        <title>Decompositional Argument Mining: A General Purpose Approach for Argument Graph Construction</title>
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    <abstract>This work presents an approach decomposing propositions into four functional components and identify the patterns linking those components to determine argument structure. The entities addressed by a proposition are target concepts and the features selected to make a point about the target concepts are aspects. A line of reasoning is followed by providing evidence for the points made about the target concepts via aspects. Opinions on target concepts and opinions on aspects are used to support or attack the ideas expressed by target concepts and aspects. The relations between aspects, target concepts, opinions on target concepts and aspects are used to infer the argument relations. Propositions are connected iteratively to form a graph structure. The approach is generic in that it is not tuned for a specific corpus and evaluated on three different corpora from the literature: AAEC, AMT, US2016G1tv and achieved an F score of 0.79, 0.77 and 0.64, respectively.</abstract>
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%0 Conference Proceedings
%T Decompositional Argument Mining: A General Purpose Approach for Argument Graph Construction
%A Gemechu, Debela
%A Reed, Chris
%Y Korhonen, Anna
%Y Traum, David
%Y Màrquez, Lluís
%S Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
%D 2019
%8 July
%I Association for Computational Linguistics
%C Florence, Italy
%F gemechu-reed-2019-decompositional
%X This work presents an approach decomposing propositions into four functional components and identify the patterns linking those components to determine argument structure. The entities addressed by a proposition are target concepts and the features selected to make a point about the target concepts are aspects. A line of reasoning is followed by providing evidence for the points made about the target concepts via aspects. Opinions on target concepts and opinions on aspects are used to support or attack the ideas expressed by target concepts and aspects. The relations between aspects, target concepts, opinions on target concepts and aspects are used to infer the argument relations. Propositions are connected iteratively to form a graph structure. The approach is generic in that it is not tuned for a specific corpus and evaluated on three different corpora from the literature: AAEC, AMT, US2016G1tv and achieved an F score of 0.79, 0.77 and 0.64, respectively.
%R 10.18653/v1/P19-1049
%U https://aclanthology.org/P19-1049
%U https://doi.org/10.18653/v1/P19-1049
%P 516-526

Markdown (Informal)

[Decompositional Argument Mining: A General Purpose Approach for Argument Graph Construction](https://aclanthology.org/P19-1049) (Gemechu & Reed, ACL 2019)

• Decompositional Argument Mining: A General Purpose Approach for Argument Graph Construction (Gemechu & Reed, ACL 2019)

ACL

• Debela Gemechu and Chris Reed. 2019. Decompositional Argument Mining: A General Purpose Approach for Argument Graph Construction. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pages 516–526, Florence, Italy. Association for Computational Linguistics.