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      SemEval 2023 Task 6: LegalEval -- Understanding Legal Texts

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          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.

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          Author and article information

          Journal
          19 April 2023
          Article
          2304.09548
          ec4952f0-0371-43ee-95e6-3d1e77b84892

          http://creativecommons.org/licenses/by-nc-sa/4.0/

          History
          Custom metadata
          13 Pages (9 Pages + References), Accepted at SemEval 2023
          cs.CL cs.AI cs.LG

          Theoretical computer science,Artificial intelligence
          Theoretical computer science, Artificial intelligence

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