Steno AI at SemEval-2023 Task 6: Rhetorical Role Labelling of Legal Documents using Transformers and Graph Neural Networks
Anshika Gupta, Shaz Furniturewala, Vijay Kumari, Yashvardhan Sharma
Abstract
A legal document is usually long and dense requiring human effort to parse it. It also contains significant amounts of jargon which make deriving insights from it using existing models a poor approach. This paper presents the approaches undertaken to perform the task of rhetorical role labelling on Indian Court Judgements. We experiment with graph based approaches like Graph Convolutional Networks and Label Propagation Algorithm, and transformer-based approaches including variants of BERT to improve accuracy scores on text classification of complex legal documents.- Anthology ID:
- 2023.semeval-1.256
- Volume:
- Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)
- Month:
- July
- Year:
- 2023
- Address:
- Toronto, Canada
- Editors:
- Atul Kr. Ojha, A. Seza Doğruöz, Giovanni Da San Martino, Harish Tayyar Madabushi, Ritesh Kumar, Elisa Sartori
- Venue:
- SemEval
- SIG:
- SIGLEX
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 1858–1862
- Language:
- URL:
- https://aclanthology.org/2023.semeval-1.256
- DOI:
- 10.18653/v1/2023.semeval-1.256
- Cite (ACL):
- Anshika Gupta, Shaz Furniturewala, Vijay Kumari, and Yashvardhan Sharma. 2023. Steno AI at SemEval-2023 Task 6: Rhetorical Role Labelling of Legal Documents using Transformers and Graph Neural Networks. In Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023), pages 1858–1862, Toronto, Canada. Association for Computational Linguistics.
- Cite (Informal):
- Steno AI at SemEval-2023 Task 6: Rhetorical Role Labelling of Legal Documents using Transformers and Graph Neural Networks (Gupta et al., SemEval 2023)
- PDF:
- https://preview.aclanthology.org/proper-vol2-ingestion/2023.semeval-1.256.pdf