mlsanityData to 14 Oct 2026

SemEval 2023 Task 6: LegalEval - Understanding Legal Texts

arXiv 2304.09548 ↗First posted 19 Apr 2023cs.CL cs.AI cs.LGcited by 7

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Abstract (arXiv)

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.

Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). Builds on 26 of its 68 references that are in the map. First posted on arXiv 19 Apr 2023.

Builds on

26 of 68 references.

References · 26

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14 more
  1. 2019Neural Legal Judgment Prediction in Englishcited by 209
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Citing papers per year: 2023: 3; 2024: 3; 2025: 1.

7 papers.