IndianBailJudgments-1200: A Multi-Attribute Dataset for Legal NLP on Indian Bail Orders

Sneha Deshmukh, Prathmesh Kamble
7/3/2025
cs.CLcs.AIcs.LG

No confident code implementation found for this paper.

Abstract

Legal NLP remains underdeveloped in regions like India due to the scarcity of structured datasets. We introduce IndianBailJudgments-1200, a new benchmark dataset comprising 1200 Indian court judgments on bail decisions, annotated across 20+ attributes including bail outcome, IPC sections, crime type, and legal reasoning. Annotations were generated using a prompt-engineered GPT-4o pipeline and verified for consistency. This resource supports a wide range of legal NLP tasks such as outcome prediction, summarization, and fairness analysis, and is the first publicly available dataset focused specifically on Indian bail jurisprudence.

View on arXivView PDF

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. Any repos shown below are weak matches — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Similar Papers

IBPS: Indian Bail Prediction System

87% match2025

NyayaAnumana & INLegalLlama: The Largest Indian Legal Judgment Prediction Dataset and Specialized Language Model for Enhanced Decision Analysis

84% match2024

IL-TUR: Benchmark for Indian Legal Text Understanding and Reasoning

83% match2024

Legal Judgment Reimagined: PredEx and the Rise of Intelligent AI Interpretation in Indian Courts

83% match1 repo62024

ILSIC: Corpora for Identifying Indian Legal Statutes from Queries by Laypeople

81% match2026

TathyaNyaya and FactLegalLlama: Advancing Factual Judgment Prediction and Explanation in the Indian Legal Context

81% match1 repo12025

Cite this paper

@article{deshmukh2025indianbailjudgments,
  title  = {IndianBailJudgments-1200: A Multi-Attribute Dataset for Legal NLP on Indian Bail Orders},
  author = {Sneha Deshmukh and Prathmesh Kamble},
  year   = {2025},
  eprint = {2507.02506},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2507.02506v1}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2507.02506.svg)](https://codeofpaper.com/paper/2507.02506)

Discussion