CLAIIRLGOct 17, 2023

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

arXiv:2310.11049v1224 citationsh-index: 27
Originality Synthesis-oriented
AI Analysis

This work addresses the need to automate legal analysis, but it is incremental as it applies existing methods to new data in a competition setting.

The paper tackled legal text understanding tasks in SemEval-2023 Task 6, achieving competitive rankings including 1st place in Court Judgment Prediction with Explanation.

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.

Code Implementations1 repo
Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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