SemEval 2023 Task 6: LegalEval - Understanding Legal Texts

Autor:	Modi, Ashutosh, Kalamkar, Prathamesh, Karn, Saurabh, Tiwari, Aman, Joshi, Abhinav, Tanikella, Sai Kiran, Guha, Shouvik Kumar, Malhan, Sachin, Raghavan, Vivek
Rok vydání:	2023
Předmět:	Computer Science - Computation and Language Computer Science - Artificial Intelligence Computer Science - Machine Learning
Druh dokumentu:	Working Paper
Popis:	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. Comment: 13 Pages (9 Pages + References), Accepted at SemEval 2023 at ACL 2023
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2304.09548 Zobrazit plný text záznamu View this record from Arxiv