---
license: mit
language:
- my
tags:
- burmese
- myanmar
- nlp
- corpus
- wikisource
task_categories:
- text-generation
- fill-mask
- translation
- summarization
size_categories:
- 1M<n<10M
---
# DatarrX MyWikisource Corpus

A high-quality, large-scale Burmese (Myanmar) language dataset extracted and refined from the official **Burmese Wikisource**. This dataset is specifically designed for Natural Language Processing (NLP) tasks, including language modeling, spell checking, and formal text analysis.

## Dataset Summary
- **Organization:** [DatarrX](https://huggingface.co/DatarrX)
- **Maintainer:** [Khant Sint Heinn(Kalix Louis)](https://huggingface.co/kalixlouiis)
- **Source:** [Burmese Wikisource (my.wikisource.org)](https://my.wikisource.org/)
- **Total Rows:** 1,352,972
- **Total Rows:** 1,352,972
- **Format:** ID, Categories, Title, Context
- **Language:** Burmese (Myanmar) - 100% (Threshold Filtered)
- **License:** MIT
  
## Data Origin (Source)
The data is sourced directly from the **Wikimedia Foundation's Wikisource project for the Burmese language**. Wikisource is a digital library of free-content textual sources, which includes historical documents, classical literature, legal texts, and poems that have been proofread by the community.

## Data Processing Details
This dataset has undergone rigorous cleaning to ensure high utility for AI/ML applications:

1.  **Namespace Filtering:** Only core encyclopedia/document entries (NS:0) were included, removing metadata and talk pages.
2.  **HTML/XML Cleaning:** All residual tags (e.g., `<p>`, `<div>`, etc.) have been removed using regex patterns.
3.  **Language Threshold:** A strict 70% Burmese character threshold was applied to every row to filter out heavy English or foreign language noise.
4.  **Deduplication:** Repeated contexts and duplicate entries were removed to prevent model overfitting.
5.  **Sentence Refinement:** - Sentences are split based on the Burmese period (။).
    - Extremely short fragments (less than 10 characters) were intelligently merged with adjacent sentences to maintain contextual meaning.
6.  **Noise Mitigation:** Known noise patterns like "မေး။ ။" and "ဖြေ။ ။" have been stripped out. 

> **Note:** While significant efforts were made to clean the data, users might still encounter minor noise due to the nature of historical transcriptions in the source material.

## Dataset Structure
| Column | Description |
| :--- | :--- |
| `id` | Unique sequential identifier for each row. |
| `categories` | Categories assigned to the original Wikisource article. |
| `title` | The title of the original article/document. |
| `context` | The cleaned Burmese sentence or paragraph. |

## Licensing Information
This dataset is released under the **MIT License**. You are free to use, modify, and distribute it, provided that the original credit is given to the creators.

## Contribution & Support
Developed by **Kalix Louiis** under the **DatarrX** organization. We aim to build robust open-source datasets for the Burmese NLP ecosystem.

- **Organization Profile:** [DatarrX](https://huggingface.co/DatarrX)
- **Author Profile:** [Khant Sint Heinn(Kalix Louis)](https://huggingface.co/kalixlouiis)

If you find this dataset useful, please consider giving it a ❤️ on the Hugging Face repository!

## Citation
If you use this dataset, please cite it using the following formats:

**APA:**
Khant Sint Heinn (Kalix Louis). (2026). MyWikisource: A Large-Scale High-Quality Burmese Corpus (Version 1.0) [Data set]. DatarrX. https://huggingface.co/datasets/DatarrX/mywikisource

```BibTeX
@dataset{khant_sint_heinn_2026_mywikisource,
  author       = {Khant Sint Heinn (Kalix Louis)},
  title        = {MyWikisource: A Large-Scale High-Quality Burmese Corpus},
  year         = {2026},
  publisher    = {Hugging Face},
  organization = {DatarrX},
  version      = {1.0},
  url          = {https://huggingface.co/datasets/DatarrX/mywikisource}
}
```

## About the Author

**Khant Sint Heinn**, working under the name **Kalix Louis**, is a **Machine Learning Engineer focused on Natural Language Processing (NLP), data foundations, and open-source AI development**. His work is centered on improving support for the Burmese (Myanmar) language in modern AI systems by building high-quality datasets, practical tools, and scalable infrastructure for language technology.

He is currently the **Lead Developer at DatarrX**, where he develops data pipelines, manages large-scale data collection workflows, and helps create open-source resources for researchers, developers, and organizations. His experience includes data engineering, web scripting, dataset curation, and building systems that support real-world machine learning applications.

Khant Sint Heinn is especially interested in advancing low-resource languages and making AI more accessible to underrepresented communities. Through his open-source contributions, he works to strengthen the Burmese (Myanmar) tech ecosystem and provide reliable building blocks for future language models, search systems, and intelligent applications.

His goal is simple: to turn limited language resources into practical opportunities through clean data, useful tools, and community-driven innovation.

**Connect with the Author:**  
[GitHub](https://github.com/kalixlouiis) | [Hugging Face](https://huggingface.co/kalixlouiis) | [Kaggle](https://www.kaggle.com/organizations/kalixlouiis)