End-to-End Argument Mining for Discussion Threads Based on Parallel Constrained Pointer Architecture

Gaku Morio, Katsuhide Fujita


Abstract
Argument Mining (AM) is a relatively recent discipline, which concentrates on extracting claims or premises from discourses, and inferring their structures. However, many existing works do not consider micro-level AM studies on discussion threads sufficiently. In this paper, we tackle AM for discussion threads. Our main contributions are follows: (1) A novel combination scheme focusing on micro-level inner- and inter- post schemes for a discussion thread. (2) Annotation of large-scale civic discussion threads with the scheme. (3) Parallel constrained pointer architecture (PCPA), a novel end-to-end technique to discriminate sentence types, inner-post relations, and inter-post interactions simultaneously. The experimental results demonstrate that our proposed model shows better accuracy in terms of relations extraction, in comparison to existing state-of-the-art models.
Anthology ID:
W18-5202
Volume:
Proceedings of the 5th Workshop on Argument Mining
Month:
November
Year:
2018
Address:
Brussels, Belgium
Venue:
ArgMining
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
11–21
Language:
URL:
https://aclanthology.org/W18-5202
DOI:
10.18653/v1/W18-5202
Bibkey:
Cite (ACL):
Gaku Morio and Katsuhide Fujita. 2018. End-to-End Argument Mining for Discussion Threads Based on Parallel Constrained Pointer Architecture. In Proceedings of the 5th Workshop on Argument Mining, pages 11–21, Brussels, Belgium. Association for Computational Linguistics.
Cite (Informal):
End-to-End Argument Mining for Discussion Threads Based on Parallel Constrained Pointer Architecture (Morio & Fujita, ArgMining 2018)
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PDF:
https://aclanthology.org/W18-5202.pdf