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

被引：0

作者：

Nigam, Shubham Kumar ^{[1
]}

Deroy, Aniket ^{[2
]}

Shallum, Noel ^{[3
]}

Mishra, Ayush Kumar ^{[1
]}

Roy, Anup ^{[1
]}

Mishra, Shubham Kumar ^{[1
]}

Bhattacharya, Arnab ^{[1
]}

Ghosh, Saptarshi ^{[2
]}

Ghosh, Kripabandhu ^{[4
]}

机构：

[1] IIT Kanpur, Kanpur, Uttar Pradesh, India

[2] IIT Kharagpur, Kharagpur, W Bengal, India

[3] Symbiosis Law Sch Pune, Pune, Maharashtra, India

[4] IISER Kolkata, Kolkata, India

来源：

17TH INTERNATIONAL WORKSHOP ON SEMANTIC EVALUATION, SEMEVAL-2023 | 2023年

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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 15th, 11th, and 1st in Task-B, Task-C1, and Task-C2, respectively, as reported on the leaderboard.

引用

页码：1293 / 1303

页数：11

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