Argument Relation Classification Using a Joint Inference Model

Yufang Hou, Charles Jochim


Abstract
In this paper, we address the problem of argument relation classification where argument units are from different texts. We design a joint inference method for the task by modeling argument relation classification and stance classification jointly. We show that our joint model improves the results over several strong baselines.
Anthology ID:
W17-5107
Volume:
Proceedings of the 4th Workshop on Argument Mining
Month:
September
Year:
2017
Address:
Copenhagen, Denmark
Editors:
Ivan Habernal, Iryna Gurevych, Kevin Ashley, Claire Cardie, Nancy Green, Diane Litman, Georgios Petasis, Chris Reed, Noam Slonim, Vern Walker
Venue:
ArgMining
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
60–66
Language:
URL:
https://aclanthology.org/W17-5107
DOI:
10.18653/v1/W17-5107
Bibkey:
Cite (ACL):
Yufang Hou and Charles Jochim. 2017. Argument Relation Classification Using a Joint Inference Model. In Proceedings of the 4th Workshop on Argument Mining, pages 60–66, Copenhagen, Denmark. Association for Computational Linguistics.
Cite (Informal):
Argument Relation Classification Using a Joint Inference Model (Hou & Jochim, ArgMining 2017)
Copy Citation:
PDF:
https://aclanthology.org/W17-5107.pdf