New Sinhala OCR dataset from 1981-2019 legislative acts enables LightOnOCR-2-1B to reach 1.05% CER, beating Surya-OCR, Tesseract, and Google Document AI.
Sri Lanka Document Datasets: A Large-Scale, Multilingual Resource for Law, News, and Policy
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
abstract
We present a collection of open, machine-readable document datasets covering parliamentary proceedings, legal judgments, government publications, news, and tourism statistics from Sri Lanka. The collection currently comprises of 269,194 documents (79.5 GB) across 26 datasets in Sinhala, Tamil, and English. The datasets are updated daily and mirrored on GitHub and Hugging Face. These resources aim to support research in computational linguistics, legal analytics, socio-political studies, and multilingual natural language processing. We describe the data sources, collection pipeline, formats, and potential use cases, while discussing licensing and ethical considerations. This manuscript is at version v2026-05-15-0811.
fields
cs.CL 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Cross-Temporal Sinhala OCR: Page-Level Adaptation and Diachronic Analysis
New Sinhala OCR dataset from 1981-2019 legislative acts enables LightOnOCR-2-1B to reach 1.05% CER, beating Surya-OCR, Tesseract, and Google Document AI.