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
Venues:
ArgMining | EMNLP | WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
11–21
Language:
URL:
https://www.aclweb.org/anthology/W18-5202
DOI:
10.18653/v1/W18-5202
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PDF:
http://aclanthology.lst.uni-saarland.de/W18-5202.pdf