no code implementations • 25 Jan 2024 • Amit Barman, Devangan Roy, Debapriya Paul, Indranil Dutta, Shouvik Kumar Guha, Samir Karmakar, Sudip Kumar Naskar
There is an evident lack of implementation of Machine Learning (ML) in the legal domain in India, and any research that does take place in this domain is usually based on data from the higher courts of law and works with English data.
no code implementations • 19 Apr 2023 • Ashutosh Modi, Prathamesh Kalamkar, Saurabh Karn, Aman Tiwari, Abhinav Joshi, Sai Kiran Tanikella, Shouvik Kumar Guha, Sachin Malhan, Vivek Raghavan
LegalEval task has three sub-tasks: Task-A (Rhetorical Roles Labeling) is about automatically structuring legal documents into semantically coherent units, Task-B (Legal Named Entity Recognition) deals with identifying relevant entities in a legal document and Task-C (Court Judgement Prediction with Explanation) explores the possibility of automatically predicting the outcome of a legal case along with providing an explanation for the prediction.
1 code implementation • 3 Dec 2021 • Vijit Malik, Rishabh Sanjay, Shouvik Kumar Guha, Angshuman Hazarika, Shubham Nigam, Arnab Bhattacharya, Ashutosh Modi
For automatically segmenting the legal documents, we experiment with the task of rhetorical role prediction: given a document, predict the text segments corresponding to various roles.
1 code implementation • ACL 2021 • Vijit Malik, Rishabh Sanjay, Shubham Kumar Nigam, Kripa Ghosh, Shouvik Kumar Guha, Arnab Bhattacharya, Ashutosh Modi
The task requires an automated system to predict an explainable outcome of a case.