End-to-End Argument Mining for Discussion Threads Based on Parallel Constrained Pointer Architecture
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
- 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)
- PDF:
- https://preview.aclanthology.org/auto-file-uploads/W18-5202.pdf