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
- 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)
- PDF:
- https://preview.aclanthology.org/emnlp-22-attachments/W19-4504.pdf