---
language:
- my
license: cc-by-4.0
tags:
- myanmar
- burmese
- history
- nlp
- text-classification
- rag
pretty_name: Open Myanmar Data - Myanmar Kings & Historical Narrative Dataset
dataset_info:
  features:
  - name: row_id
    dtype: string
  - name: source_topic
    dtype: string
  - name: sentence
    dtype: string
  - name: data_type
    dtype: string
  splits:
  - name: train
    num_bytes: 587678
    num_examples: 1242
    download_size: 174897
    dataset_size: 587678
  configs:
  - config_name: default
    data_files:
    - split: train
      path: data/train-*
---

# 🇲🇲 Open Myanmar Data: Myanmar Kings & Historical Narrative Dataset

[![License: CC BY 4.0](https://img.shields.io/badge/License-CC_BY_4.0-lightgrey.svg)](https://creativecommons.org/licenses/by/4.0/)
[![Hugging Face](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Datasets-blue)](https://huggingface.co/datasets)

## 📌 Dataset Summary
This repository contains a clean, high-quality, sentence-segmented historical narrative dataset regarding Myanmar history, royal dynasties (Pagan, Toungoo, Konbaung), and notable historical figures extracted directly from Myanmar Wikipedia.

Curated and cleaned by **Aung Ko Ko Oo** (Founder, Burmese NLP Research Group).

---

## 📊 Dataset Overview
- **Total Sentences:** `1,242`
- **Duplication Rate:** `0.00%` (100% unique clean sentences)
- **Data Type:** `Historical Narrative`
- **Source:** Myanmar Wikipedia (Attribution under CC BY-SA 4.0)

---

## 📂 Dataset Structure

| Column | Data Type | Description |
| :--- | :--- | :--- |
| `row_id` | String | Unique identifier (e.g., `MY_HIST_00001`) |
| `source_topic` | String | Wikipedia topic/entity title |
| `sentence` | String | Clean Myanmar sentence ending with standard boundary (`။`) |
| `data_type` | String | Text category (`Historical Narrative`) |

---

## 💡 Intended Use Cases
1. **Retrieval-Augmented Generation (RAG):** Knowledge indexing for Burmese historical QA chatbots.
2. **Sentence Embedding & Vector Search:** Benchmarking Burmese semantic similarity and clustering.
3. **Information Extraction (IE):** Named Entity Recognition (NER) and Relation Extraction for Burmese history.

---

## 💻 How to Use

### 1. Load via Hugging Face `datasets` Library
```python
from datasets import load_dataset

# Load from Hugging Face Hub
dataset = load_dataset("austin2029/open-myanmar-data")
print(dataset['train'][0])

import pandas as pd

df = pd.read_csv("myanmar_kings/myanmar_kings_dataset.csv")
print(df.head())

@misc{open_myanmar_data_2026,
  author = {Aung Ko Ko Oo},
  title = {Open Myanmar Data: Myanmar Kings & Historical Narrative Dataset},
  year = {2026},
  publisher = {GitHub / Hugging Face},
  howpublished = {\url{[https://github.com/Aung-Ko-Ko-Oo/open-myanmar-data](https://github.com/Aung-Ko-Ko-Oo/open-myanmar-data)}}
}