Pungene at DialAM-2024: Identification of Propositional and Illocutionary Relations
Sirawut Chaixanien, Eugene Choi, Shaden Shaar, Claire Cardie
Abstract
In this paper we tackle the shared task DialAM-2024 aiming to annotate dialogue based on the inference anchoring theory (IAT). The task can be split into two parts, identification of propositional relations and identification of illocutionary relations. We propose a pipelined system made up of three parts: (1) locutionary-propositions relation detection, (2) propositional relations detection, and (3) illocutionary relations identification. We fine-tune models independently for each step, and combine at the end for the final system. Our proposed system ranks second overall compared to other participants in the shared task, scoring an average f1-score on both sub-parts of 63.7.- Anthology ID:
- 2024.argmining-1.12
- Volume:
- Proceedings of the 11th Workshop on Argument Mining (ArgMining 2024)
- Month:
- August
- Year:
- 2024
- Address:
- Bangkok, Thailand
- Editors:
- Yamen Ajjour, Roy Bar-Haim, Roxanne El Baff, Zhexiong Liu, Gabriella Skitalinskaya
- Venue:
- ArgMining
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 119–123
- Language:
- URL:
- https://aclanthology.org/2024.argmining-1.12
- DOI:
- 10.18653/v1/2024.argmining-1.12
- Cite (ACL):
- Sirawut Chaixanien, Eugene Choi, Shaden Shaar, and Claire Cardie. 2024. Pungene at DialAM-2024: Identification of Propositional and Illocutionary Relations. In Proceedings of the 11th Workshop on Argument Mining (ArgMining 2024), pages 119–123, Bangkok, Thailand. Association for Computational Linguistics.
- Cite (Informal):
- Pungene at DialAM-2024: Identification of Propositional and Illocutionary Relations (Chaixanien et al., ArgMining 2024)
- PDF:
- https://preview.aclanthology.org/autopr/2024.argmining-1.12.pdf