Decompositional Argument Mining: A General Purpose Approach for Argument Graph Construction

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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.
Original languageEnglish
Title of host publicationProceedings of the 57th Annual Meeting of the Association for Computational Linguistics
Place of PublicationFlorence, Italy
PublisherAssociation for Computational Linguistics
Pages516-526
Number of pages11
VolumeP19-1049
DOIs
Publication statusPublished - 2019
Event57th Annual Meeting of the Association for Computational Linguistics - Florence, Italy
Duration: 1 Jul 20191 Jul 2019

Conference

Conference57th Annual Meeting of the Association for Computational Linguistics
CountryItaly
CityFlorence
Period1/07/191/07/19

Profiles

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Reed, Chris

  • Computing - Professor & Personal Chair of Computer Science and Philosophy

Person: Academic

Cite this

Gemechu, D., & Reed, C. (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 (Vol. P19-1049, pp. 516-526). Association for Computational Linguistics. https://doi.org/10.18653/v1/P19-1049