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Pakistani Law Dataset: Structured Legal Acts of Pakistan (Criminal, Family, and Property Law)

This dataset contains structured and machine-readable data extracted from 8 major Pakistani legal documents, parsed from official PDF versions. It covers Family Law, Criminal Law, Civil Procedure, Property Law, and Evidence Law. Designed for use in legal AI, RAG <b

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CreatorAhmed, Umair
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Published2026-06-02
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DOI10.5281/zenodo.20509007
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Downloads377
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Licensecc-by-4.0
File Size5.1 MB
Data TypeDataset
Published2026
Licensecc-by-4.0
Total Views219
Total Downloads377

This dataset contains structured and machine-readable data extracted 
from 8 major Pakistani legal documents, parsed from official PDF 
versions. It covers Family Law, Criminal Law, Civil Procedure, 
Property Law, and Evidence Law. Designed for use in legal AI, RAG 
pipelines, and LLM fine-tuning.

Built as part of the paper:
“Enhancing Legal Assistance with Large Language Models: A 
Parameter-Efficient Fine-Tuning and Retrieval-Augmented Generation 
Approach” — Ahmed et al., submitted to PLOS ONE, 2025.

Files included:
– combined_legal_dataset.csv: Merged file combining all laws
– 2-limitation-act-1908: Legal time limits for civil suits
– Code_of_Criminal_Procedure: Procedural rules for criminal trials
– Muslim_Family_Laws_Ordinance_1961: Marriage, divorce, inheritance
– Pakistan_Penal_Code: Penal offenses and punishments
– Police_law: Police powers and duties
– Transfer_property: Property transfer, sales, mortgage, lease
– qanun-e-shahadat_1984: Law of evidence

All files follow schema: Book | Chapter Number | Chapter Title | 
Section | Heading | Definition

For research purposes only. Not a substitute for professional legal 
advice.

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Pakistani Law Dataset: Structured Legal Acts of Pakistan… (Full Dataset)5.1 MB
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ReadmeVia DOI record
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Files are hosted on the source repository. Click download to access the full dataset.

Ahmed, Umair (2026). Pakistani Law Dataset: Structured Legal Acts of Pakistan (Criminal, Family, and Property Law). https://doi.org/10.5281/zenodo.20509007