Legal Argument Extraction from Court Judgements using Integer Linear Programming
Basit Ali, Sachin Pawar, Girish Palshikar, Anindita Sinha Banerjee, Dhirendra Singh
Abstract
Legal arguments are one of the key aspects of legal knowledge which are expressed in various ways in the unstructured text of court judgements. A large database of past legal arguments can be created by extracting arguments from court judgements, categorizing them, and storing them in a structured format. Such a database would be useful for suggesting suitable arguments for any new case. In this paper, we focus on extracting arguments from Indian Supreme Court judgements using minimal supervision. We first identify a set of certain sentence-level argument markers which are useful for argument extraction such as whether a sentence contains a claim or not, whether a sentence is argumentative in nature, whether two sentences are part of the same argument, etc. We then model the legal argument extraction problem as a text segmentation problem where we combine multiple weak evidences in the form of argument markers using Integer Linear Programming (ILP), finally arriving at a global document-level solution giving the most optimal legal arguments. We demonstrate the effectiveness of our technique by comparing it against several competent baselines.- Anthology ID:
- 2023.argmining-1.6
- Volume:
- Proceedings of the 10th Workshop on Argument Mining
- Month:
- December
- Year:
- 2023
- Address:
- Singapore
- Editors:
- Milad Alshomary, Chung-Chi Chen, Smaranda Muresan, Joonsuk Park, Julia Romberg
- Venues:
- ArgMining | WS
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 52–63
- Language:
- URL:
- https://aclanthology.org/2023.argmining-1.6
- DOI:
- 10.18653/v1/2023.argmining-1.6
- Cite (ACL):
- Basit Ali, Sachin Pawar, Girish Palshikar, Anindita Sinha Banerjee, and Dhirendra Singh. 2023. Legal Argument Extraction from Court Judgements using Integer Linear Programming. In Proceedings of the 10th Workshop on Argument Mining, pages 52–63, Singapore. Association for Computational Linguistics.
- Cite (Informal):
- Legal Argument Extraction from Court Judgements using Integer Linear Programming (Ali et al., ArgMining-WS 2023)
- PDF:
- https://preview.aclanthology.org/naacl24-info/2023.argmining-1.6.pdf