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

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 discuss...

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Bibliographic Details
Published inarXiv.org
Main Authors Morio, Gaku, Fujita, Katsuhide
Format Paper
LanguageEnglish
Published Ithaca Cornell University Library, arXiv.org 03.09.2018
Subjects
Annotations
Architecture
Model accuracy
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Summary: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.
ISSN:2331-8422