1 research outputs found
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 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.Comment: accepted at the 5th Workshop on Argument Mining at EMNLP 201