README.md

---
license: cc-by-nc-sa-4.0
language:
  - en
  - my
pretty_name: "Myanmar Bilingual Village Address Directory (72k+ Entries)"
tags:
  - myanmar
  - bilingual
  - geospatial
  - address-parsing
  - named-entity-recognition
  - translation
configs:
- config_name: default
  data_files:
  - split: train
    path: myanmar_village_based_72k_addresses.csv
---

# Myanmar Bilingual Village Address Directory (72k+ Entries)

## Dataset Description

This dataset provides a comprehensive, bilingual (English and Myanmar) list of over 72,000 rural village addresses across Myanmar. Each entry is a clean, human-readable address string containing the village, village tract, township, district, and state/region.

The dataset is ideal for a wide range of NLP and data science tasks, including Named Entity Recognition (NER), address parsing, machine translation, and as a foundational resource for logistics and geospatial analysis in the Myanmar context.

This final, cleaned dataset was prepared by [freococo](https://huggingface.co/freococo).

## Data Fields

The dataset contains a single CSV file (`myanmar_village_based_72k_addresses.csv`) with two columns, representing a parallel corpus of addresses.

*   `Address_English`: The complete address string in English.
*   `Address_Myanmar`: The complete address string in Myanmar script.

**Example Row:**
| Address_English | Address_Myanmar |
|---|---|
| `Da None Chaung, (Kyun Nyo Gyi) Kyun Hteik, Bogale Township, Pyapon District, Ayeyarwady` | `ဓနုံးချောင်း, (ကျွန်းညိုကြီး) ကျွန်းထိပ် ကျေးရွာအုပ်စု, ဘိုကလေး မြို့နယ်, ဖျာပုံခရိုင်, ဧရာဝတီတိုင်းဒေသကြီး` |

## Data Splits

The dataset consists of a single split, `train`, containing 72,569 entries.

## Dataset Creation

The dataset was derived from the **Myanmar Place Codes (P-Codes) Release 9.6 (Feb 2025)**, provided by the **Myanmar Information Management Unit (MIMU)**, a service of the United Nations in Myanmar. The source data was downloaded from the **Humanitarian Data Exchange (HDX)**.

The original hierarchical files were programmatically merged, de-duplicated, and transformed into this clean, flat address list using Python and the pandas library.

## Usage

The dataset can be easily loaded using the Hugging Face `datasets` library.

```python
from datasets import load_dataset

# Load the dataset
dataset = load_dataset("freococo/myanmar_village_based_72k_addresses")

# Access an example from the dataset
print(dataset['train'])

# Expected output:
# {
#  'Address_English': 'Da None Chaung, (Kyun Nyo Gyi) Kyun Hteik, Bogale Township, Pyapon District, Ayeyarwady',
#  'Address_Myanmar': 'ဓနုံးချောင်း, (ကျွန်းညိုကြီး) ကျွန်းထိပ် ကျေးရွာအုပ်စု, ဘိုကလေး မြို့နယ်, ဖျာပုံခရိုင်, ဧရာဝတီတိုင်းဒေသကြီး'
# }
```
## Use Cases and Limitations

### Potential Use Cases

*   **Named Entity Recognition (NER):** This dataset is a valuable resource for training models to recognize Myanmar place names (e.g., `B-STATE`, `I-DISTRICT`, `I-VILLAGE`).
*   **Address Parsing:** It can be used to train models that can take an unstructured address string and break it down into its constituent administrative parts (village, township, etc.).
*   **Machine Translation:** The bilingual format makes it a useful parallel corpus for fine-tuning translation models specifically for Myanmar administrative terms.
*   **Data Augmentation:** Can be used to create realistic synthetic data for applications requiring Myanmar addresses.

### Limitations

*   **Rural Only:** This dataset exclusively contains rural village addresses and does not include urban administrative units like towns or wards.
*   **No Geographic Coordinates:** The final formatted file does not contain latitude and longitude data. For geocoding, this dataset would need to be joined back to the original source files.
*   **Static Data:** The dataset is based on the February 2025 release from MIMU and will not reflect any subsequent administrative changes.

## Citation Information

If you use this dataset in your work, please cite the original data source and acknowledge the creator of this specific version.

### Citing the Original Source

> Myanmar Information Management Unit (MIMU). (2025). *MIMU Place Codes (P-Codes) Release 9.6*. Sourced from the Humanitarian Data Exchange (HDX).

### Citing this Dataset Repository

```bibtex
@dataset{freococo_myanmar_village_addresses,
  author = {freococo},
  title = {Myanmar Bilingual Village Address Directory (72k+ Entries)},
  year = {2025},
  publisher = {Hugging Face},
  version = {1.0.0},
  url = {https://huggingface.co/datasets/freococo/myanmar_village_based_72k_addresses}
}