# SinhaLegal: A Benchmark Corpus for Information Extraction and Analysis in Sinhala Legislative Texts

arXiv: https://arxiv.org/abs/2603.04854 · HTML: https://mlsanity.com/paper/2603.04854/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 19 of its 43 references that are in the map.
- First posted on arXiv 5 Mar 2026.

## Builds on (most cited first, 19 of 19)

- [RoBERTa: A Robustly Optimized BERT Pretraining Approach](https://mlsanity.com/paper/1907.11692/) (2019)
- [The Falcon Series of Open Language Models](https://mlsanity.com/paper/2311.16867/) (2023)
- [BIGPATENT: A Large-Scale Dataset for Abstractive and Coherent Summarization](https://mlsanity.com/paper/1906.03741/) (2019)
- [ILDC for CJPE: Indian Legal Documents Corpus for Court Judgment Prediction and Explanation](https://mlsanity.com/paper/2105.13562/) (2021)
- [Language Model Evaluation Beyond Perplexity](https://mlsanity.com/paper/2106.00085/) (2021)
- [MultiLegalPile: A 689GB Multilingual Legal Corpus](https://mlsanity.com/paper/2306.02069/) (2023)
- [Survey on Publicly Available Sinhala Natural Language Processing Tools and Research](https://mlsanity.com/paper/1906.02358/) (2019)
- [Natural Language Processing for the Legal Domain: A Survey of Tasks, Datasets, Models, and Challenges](https://mlsanity.com/paper/2410.21306/) (2024)
- [Understanding the Repeat Curse in Large Language Models from a Feature Perspective](https://mlsanity.com/paper/2504.14218/) (2025)
- [A Dataset of German Legal Documents for Named Entity Recognition](https://mlsanity.com/paper/2003.13016/) (2020)
- [How Many Topics? Stability Analysis for Topic Models](https://mlsanity.com/paper/1404.4606/) (2014)
- [The Cambridge Law Corpus: A Dataset for Legal AI Research](https://mlsanity.com/paper/2309.12269/) (2023)
- [Zero-shot OCR Accuracy of Low-Resourced Languages: A Comparative Analysis on Sinhala and Tamil](https://mlsanity.com/paper/2507.18264/) (2025)
- [SinLlama -- A Large Language Model for Sinhala](https://mlsanity.com/paper/2508.09115/) (2025)
- [Japanese Tort-case Dataset for Rationale-supported Legal Judgment Prediction](https://mlsanity.com/paper/2312.00480/) (2023)
- [VLQA: The First Comprehensive, Large, and High-Quality Vietnamese Dataset for Legal Question Answering](https://mlsanity.com/paper/2507.19995/) (2025)
- [Sri Lanka Document Datasets: A Large-Scale, Multilingual Resource for Law, News, and Policy](https://mlsanity.com/paper/2510.04124/) (2025)
- [A Hybrid Architecture with Efficient Fine Tuning for Abstractive Patent Document Summarization](https://mlsanity.com/paper/2503.10354/) (2025)
- [LEGAL-UQA: A Low-Resource Urdu-English Dataset for Legal Question Answering](https://mlsanity.com/paper/2410.13013/) (2024)

## Built on by (most cited first, 1 of 1)

- [SinBrief: A Hybrid Framework for Abstractive Text Summarisation of Sinhala Legal Documents](https://mlsanity.com/paper/2609.32397/) (2026)

## Abstract (arXiv)

SinhaLegal introduces a Sinhala legislative text corpus containing approximately 2 million words across 1,206 legal documents. The dataset includes two types of legal documents: 1,065 Acts dated from 1981 to 2014 and 141 Bills from 2010 to 2014, which were systematically collected from official sources. The texts were extracted using OCR with Google Document AI, followed by extensive post-processing and manual cleaning to ensure high-quality, machine-readable content, along with dedicated metadata files for each document. A comprehensive evaluation was conducted, including corpus statistics, lexical diversity, word frequency analysis, named entity recognition, and topic modelling, demonstrating the structured and domain-specific nature of the corpus. Additionally, perplexity analysis using both large and small language models was performed to assess how effectively language models respond to domain-specific texts. The SinhaLegal corpus represents a vital resource designed to support NLP tasks such as summarisation, information extraction, and analysis, thereby bridging a critical gap in Sinhala legal research.