aiqbench analysis
This article introduces BLAD, a new dataset designed specifically to advance legal natural language processing (NLP) in low-resource South Asian contexts by providing over two centuries of multilingual legislative texts. The work addresses a critical gap in computational resources for civil-law jurisdictions, enabling researchers to build models capable of handling temporal and linguistic shifts unique to the region. By focusing on data acquisition pipelines and enrichment strategies rather than consumer applications or general software updates, this piece is squarely centered on machine learning infrastructure development.
BLAD: A Historically Contextualized, Multilingual Dataset of Bangladeshi Legal Acts (1799 to 2025)
arXiv:2607.17111v1 Announce Type: new Abstract: We present the Bangladesh Legal Acts Dataset (BLAD), a curated collection of 1{,}484 legislative acts enacted between 1799 and 2025. Each act is represented with its full text, structured sections and footnotes, repeal status, and metadata linking it to the governing regime, head of state, and prevailing legal framework at the time of enactment. The corpus spans English, Bengali, and mixed-language documents, supporting temporal and multilingual analysis of statutory law. BLAD addresses a persistent gap in legal natural language processing (NLP) resources for low-resource, civil-law jurisdictions in South Asia. We describe the acquisition and enrichment pipeline, report descriptive statistics over more than two centuries of legislation, and outline the research directions the corpus enables. The dataset is publicly available under the CC~BY-SA~4.0 license at https://www.kaggle.com/datasets/sakhadib/bangladesh-legal-acts-dataset.
Abstract:We present the Bangladesh Legal Acts Dataset (BLAD), a curated collection of 1{,}484 legislative acts enacted between 1799 and 2025. Each act is represented with its full text, structured sections and footnotes, repeal status, and metadata linking it to the governing regime, head of state, and prevailing legal framework at the time of enactment. The corpus spans English, Bengali, and mixed-language documents, supporting temporal and multilingual analysis of statutory law. BLAD addresses a persistent gap in legal natural language processing (NLP) resources for low-resource, civil-law jurisdictions in South Asia. We describe the acquisition and enrichment pipeline, report descriptive statistics over more than two centuries of legislation, and outline the research directions the corpus enables. The dataset is publicly available under the CC~BY-SA~4.0 license at this https URL.
Computation and Language (cs.CL)
arXiv:2607.17111 [cs.CL]
(or arXiv:2607.17111v1 [cs.CL] for this version)
https://doi.org/10.48550/arXiv.2607.17111 Focus to learn more arXiv-issued DOI via DataCite (pending registration)
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