IMLJD: A Computational Dataset for Indian Matrimonial Litigation Analysis

2026-05-19

AI Summary

This study addresses the scarcity of structured, computable datasets on matrimonial litigation in India, which has hindered legal artificial intelligence research. The authors present the first open-source, multi-tier structured dataset comprising 3,613 judgments from the Supreme Court of India and the Karnataka High Court, annotated with outcome labels, rich metadata, and an accompanying legal knowledge graph. Through systematic text annotation, metadata extraction, and knowledge graph construction, the dataset enables empirical cross-court and longitudinal analyses. The findings reveal that applications filed under Section 482 of the Code of Criminal Procedure to quash proceedings achieve a significantly higher success rate in the Supreme Court (57.6%) compared to the Karnataka High Court (39.7%), with a 19.6 percentage point gap persisting even after temporal matching.

Abstract

We present IMLJD, an open dataset of 3,613 Indian court judgments covering matrimonial disputes under IPC Section 498A, the Protection of Women from Domestic Violence Act, and CrPC Section 482. The dataset covers the Supreme Court of India from 2000 to 2024 (1,474 cases) and the Karnataka High Court from 2018 to 2024 (2,139 cases), with structured outcome labels, metadata-derived indicators, and a knowledge graph. We find that 57.6% of quashing petitions succeed at the Supreme Court level compared to 39.7% at the Karnataka High Court level. On a matched 2018 to 2024 period, the SC quash rate is 59.3%, widening the differential to 19.6 percentage points and confirming the finding is robust to temporal adjustment. The dataset, code, and knowledge graph are released openly at https://github.com/joyboseroy/imljd and https://huggingface.co/datasets/joyboseroy/imljd.

Problem

• matrimonial litigation
• legal dataset
• Indian court judgments
• computational law
• domestic violence

Innovation

• legal dataset
• matrimonial litigation
• knowledge graph
• judgment analysis
• computational law