SemEval 2023 Task 6: LegalEval - Understanding Legal Texts (2304.09548v3)
Abstract: In populous countries, pending legal cases have been growing exponentially. There is a need for developing NLP-based techniques for processing and automatically understanding legal documents. To promote research in the area of Legal NLP we organized the shared task LegalEval - Understanding Legal Texts at SemEval 2023. 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. In total 26 teams (approx. 100 participants spread across the world) submitted systems paper. In each of the sub-tasks, the proposed systems outperformed the baselines; however, there is a lot of scope for improvement. This paper describes the tasks, and analyzes techniques proposed by various teams.
- Ashutosh Modi (60 papers)
- Prathamesh Kalamkar (5 papers)
- Saurabh Karn (4 papers)
- Aman Tiwari (7 papers)
- Abhinav Joshi (14 papers)
- Sai Kiran Tanikella (2 papers)
- Shouvik Kumar Guha (4 papers)
- Sachin Malhan (1 paper)
- Vivek Raghavan (14 papers)