Target Inference in Argument Conclusion Generation

Milad Alshomary, Shahbaz Syed, Martin Potthast, Henning Wachsmuth


Abstract
In argumentation, people state premises to reason towards a conclusion. The conclusion conveys a stance towards some target, such as a concept or statement. Often, the conclusion remains implicit, though, since it is self-evident in a discussion or left out for rhetorical reasons. However, the conclusion is key to understanding an argument and, hence, to any application that processes argumentation. We thus study the question to what extent an argument’s conclusion can be reconstructed from its premises. In particular, we argue here that a decisive step is to infer a conclusion’s target, and we hypothesize that this target is related to the premises’ targets. We develop two complementary target inference approaches: one ranks premise targets and selects the top-ranked target as the conclusion target, the other finds a new conclusion target in a learned embedding space using a triplet neural network. Our evaluation on corpora from two domains indicates that a hybrid of both approaches is best, outperforming several strong baselines. According to human annotators, we infer a reasonably adequate conclusion target in 89% of the cases.
Anthology ID:
2020.acl-main.399
Volume:
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
Month:
July
Year:
2020
Address:
Online
Editors:
Dan Jurafsky, Joyce Chai, Natalie Schluter, Joel Tetreault
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
4334–4345
Language:
URL:
https://aclanthology.org/2020.acl-main.399
DOI:
10.18653/v1/2020.acl-main.399
Bibkey:
Cite (ACL):
Milad Alshomary, Shahbaz Syed, Martin Potthast, and Henning Wachsmuth. 2020. Target Inference in Argument Conclusion Generation. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages 4334–4345, Online. Association for Computational Linguistics.
Cite (Informal):
Target Inference in Argument Conclusion Generation (Alshomary et al., ACL 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.acl-main.399.pdf
Video:
 http://slideslive.com/38928990