license: apache-2.0
task_categories:
- text-generation
- text2text-generation
language:
- si
tags:
- articles
- books
- news
- sinhala
- wiki
- wikipedia
pretty_name: sinhala dataset
size_categories:
- 1M<n<10M
Sinhala Articles Dataset
A large-scale, high-quality Sinhala text corpus curated from diverse sources including news articles, Wikipedia entries, and general web content. This dataset is designed to support a wide range of Sinhala Natural Language Processing (NLP) tasks.
📊 Dataset Overview
- Name:
Navanjana/sinhala-articles - Total Samples: 2,148,688
- Languages: Sinhala (
si) - Features:
text: A single column containing Sinhala text passages.
- Size: Approximately 1M < n < 10M entries
- License: Apache 2.0
🧾 Dataset Structure
The dataset consists of a single split:
train: 2,148,688 entries
Each entry is a JSON object with the following structure:
{
"text": "ශ්රී ලංකාව අස්සේ ප්රසිද්ධ වූ වාර්තා මත පදනම්ව නව ගවේෂණ වැඩසටහන් ආරම්භ විය."
}
📌 Source Composition
The dataset aggregates content from:
- Sinhala News Websites: Covering current events, politics, economy, and more.
- Sinhala Wikipedia: Providing encyclopedic knowledge across various domains.
- General Web Articles: Including blogs, opinion pieces, and other informative content.
🚀 Applications
This corpus is suitable for various NLP tasks in the Sinhala language, such as:
- Language Modeling
- Text Classification
- Machine Translation
- Summarization
- Sentiment Analysis
- Named Entity Recognition
📂 Accessing the Dataset
You can load the dataset directly using the Hugging Face datasets library:
from datasets import load_dataset
dataset = load_dataset("Navanjana/sinhala-articles")
📜 License
This dataset is distributed under the Apache 2.0 License. Please ensure compliance with the terms of use of the original data sources.
🙏 Acknowledgements
We extend our gratitude to the contributors and platforms that provided the original content, enabling the creation of this comprehensive Sinhala text corpus.
📣 Citation
If you utilize this dataset in your research or applications, please cite it as follows:
@dataset{navanjana_sinhala_articles,
author = {Navanjana},
title = {Sinhala Articles Dataset},
year = {2025},
publisher = {Hugging Face},
url = {https://huggingface.co/datasets/Navanjana/sinhala-articles}
}
For more information and updates, visit the dataset page on Hugging Face.