Abstract
Legal argument reasoning task in civil procedure is a new NLP task utilizing a dataset from the domain of the U.S. civil procedure. The task aims at identifying whether the solution to a question in the legal domain is correct or not. This paper describes the team “Transformers” submission to the Legal Argument Reasoning Task in Civil Procedure shared task at SemEval-2024 Task 5. We use a BERT-based architecture for the shared task. The highest F1-score score and accuracy achieved was 0.6172 and 0.6531 respectively. We secured the 13th rank in the Legal Argument Reasoning Task in Civil Procedure shared task.- Anthology ID:
- 2024.semeval-1.140
- Volume:
- Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024)
- Month:
- June
- Year:
- 2024
- Address:
- Mexico City, Mexico
- Editors:
- Atul Kr. Ojha, A. Seza Doğruöz, Harish Tayyar Madabushi, Giovanni Da San Martino, Sara Rosenthal, Aiala Rosá
- Venue:
- SemEval
- SIG:
- SIGLEX
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 969–972
- Language:
- URL:
- https://aclanthology.org/2024.semeval-1.140
- DOI:
- Cite (ACL):
- Kriti Singhal and Jatin Bedi. 2024. Transformers at SemEval-2024 Task 5: Legal Argument Reasoning Task in Civil Procedure using RoBERTa. In Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024), pages 969–972, Mexico City, Mexico. Association for Computational Linguistics.
- Cite (Informal):
- Transformers at SemEval-2024 Task 5: Legal Argument Reasoning Task in Civil Procedure using RoBERTa (Singhal & Bedi, SemEval 2024)
- PDF:
- https://preview.aclanthology.org/corrections-2024-07/2024.semeval-1.140.pdf