An Empirical Study of Span Representations in Argumentation Structure Parsing

Tatsuki Kuribayashi, Hiroki Ouchi, Naoya Inoue, Paul Reisert, Toshinori Miyoshi, Jun Suzuki, Kentaro Inui


Abstract
For several natural language processing (NLP) tasks, span representation design is attracting considerable attention as a promising new technique; a common basis for an effective design has been established. With such basis, exploring task-dependent extensions for argumentation structure parsing (ASP) becomes an interesting research direction. This study investigates (i) span representation originally developed for other NLP tasks and (ii) a simple task-dependent extension for ASP. Our extensive experiments and analysis show that these representations yield high performance for ASP and provide some challenging types of instances to be parsed.
Anthology ID:
P19-1464
Volume:
Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
Month:
July
Year:
2019
Address:
Florence, Italy
Editors:
Anna Korhonen, David Traum, Lluís Màrquez
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
4691–4698
Language:
URL:
https://aclanthology.org/P19-1464
DOI:
10.18653/v1/P19-1464
Bibkey:
Cite (ACL):
Tatsuki Kuribayashi, Hiroki Ouchi, Naoya Inoue, Paul Reisert, Toshinori Miyoshi, Jun Suzuki, and Kentaro Inui. 2019. An Empirical Study of Span Representations in Argumentation Structure Parsing. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pages 4691–4698, Florence, Italy. Association for Computational Linguistics.
Cite (Informal):
An Empirical Study of Span Representations in Argumentation Structure Parsing (Kuribayashi et al., ACL 2019)
Copy Citation:
PDF:
https://preview.aclanthology.org/ml4al-ingestion/P19-1464.pdf