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Computer Science > Computation and Language

arXiv:2310.11049 (cs)
[Submitted on 17 Oct 2023]

Title:Nonet at SemEval-2023 Task 6: Methodologies for Legal Evaluation

Authors:Shubham Kumar Nigam, Aniket Deroy, Noel Shallum, Ayush Kumar Mishra, Anup Roy, Shubham Kumar Mishra, Arnab Bhattacharya, Saptarshi Ghosh, Kripabandhu Ghosh
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Abstract:This paper describes our submission to the SemEval-2023 for Task 6 on LegalEval: Understanding Legal Texts. Our submission concentrated on three subtasks: Legal Named Entity Recognition (L-NER) for Task-B, Legal Judgment Prediction (LJP) for Task-C1, and Court Judgment Prediction with Explanation (CJPE) for Task-C2. We conducted various experiments on these subtasks and presented the results in detail, including data statistics and methodology. It is worth noting that legal tasks, such as those tackled in this research, have been gaining importance due to the increasing need to automate legal analysis and support. Our team obtained competitive rankings of 15$^{th}$, 11$^{th}$, and 1$^{st}$ in Task-B, Task-C1, and Task-C2, respectively, as reported on the leaderboard.
Subjects: Computation and Language (cs.CL); Artificial Intelligence (cs.AI); Information Retrieval (cs.IR); Machine Learning (cs.LG)
Cite as: arXiv:2310.11049 [cs.CL]
  (or arXiv:2310.11049v1 [cs.CL] for this version)
  https://doi.org/10.48550/arXiv.2310.11049
Journal reference: https://aclanthology.org/2023.semeval-1.180
Related DOI: https://doi.org/10.18653/v1/2023.semeval-1.180

Submission history

From: Shubham Kumar Nigam [view email]
[v1] Tue, 17 Oct 2023 07:35:11 UTC (1,158 KB)
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