Aligning Discourse and Argumentation Structures using Subtrees and Redescription Mining

Laurine Huber, Yannick Toussaint, Charlotte Roze, Mathilde Dargnat, Chloé Braud


Abstract
In this paper, we investigate similarities between discourse and argumentation structures by aligning subtrees in a corpus containing both annotations. Contrary to previous works, we focus on comparing sub-structures and not only relations matches. Using data mining techniques, we show that discourse and argumentation most often align well, and the double annotation allows to derive a mapping between structures. Moreover, this approach enables the study of similarities between discourse structures and differences in their expressive power.
Anthology ID:
W19-4504
Volume:
Proceedings of the 6th Workshop on Argument Mining
Month:
August
Year:
2019
Address:
Florence, Italy
Editors:
Benno Stein, Henning Wachsmuth
Venue:
ArgMining
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
35–40
Language:
URL:
https://aclanthology.org/W19-4504
DOI:
10.18653/v1/W19-4504
Bibkey:
Cite (ACL):
Laurine Huber, Yannick Toussaint, Charlotte Roze, Mathilde Dargnat, and Chloé Braud. 2019. Aligning Discourse and Argumentation Structures using Subtrees and Redescription Mining. In Proceedings of the 6th Workshop on Argument Mining, pages 35–40, Florence, Italy. Association for Computational Linguistics.
Cite (Informal):
Aligning Discourse and Argumentation Structures using Subtrees and Redescription Mining (Huber et al., ArgMining 2019)
Copy Citation:
PDF:
https://aclanthology.org/W19-4504.pdf