README.md

---
license: cc-by-nc-sa-4.0
language: 
- khm
pretty_name: Khpos
task_categories: 
- pos-tagging
tags: 
- pos-tagging
---

The khPOS Corpus (Khmer POS Corpus) is a 12,000 sentences (25,626 words) manually word segmented and POS tagged corpus 
developed for Khmer language NLP research and developments. We collected Khmer sentences from websites that include
various area such as economics, news, politics. Moreover it is also contained some student list and voter list of 
national election committee of Cambodia. The average number of words per sentence in the whole corpus is 10.75. 
Here, some symbols such as "។" (Khmer sign Khan), "៖" (Khmer sign Camnuc pii kuuh), "-", "?", "[", "]" etc. also 
counted as words. The shortest sentence contained only 1 word and longest sentence contained 169 words. This dataset contains
A validation set and a test set, each containing 1000 sentences.


## Languages

khm

## Supported Tasks

Pos Tagging

## Dataset Usage
### Using `datasets` library
```
from datasets import load_dataset
dset = datasets.load_dataset("SEACrowd/khpos", trust_remote_code=True)
```
### Using `seacrowd` library
```import seacrowd as sc
# Load the dataset using the default config
dset = sc.load_dataset("khpos", schema="seacrowd")
# Check all available subsets (config names) of the dataset
print(sc.available_config_names("khpos"))
# Load the dataset using a specific config
dset = sc.load_dataset_by_config_name(config_name="<config_name>")
```

More details on how to load the `seacrowd` library can be found [here](https://github.com/SEACrowd/seacrowd-datahub?tab=readme-ov-file#how-to-use).


## Dataset Homepage

[https://github.com/ye-kyaw-thu/khPOS/tree/master](https://github.com/ye-kyaw-thu/khPOS/tree/master)

## Dataset Version

Source: 1.0.0. SEACrowd: 2024.06.20.

## Dataset License

Creative Commons Attribution Non Commercial Share Alike 4.0 (cc-by-nc-sa-4.0)

## Citation

If you are using the **Khpos** dataloader in your work, please cite the following:
```
@inproceedings{kyaw2017comparison,
  title={Comparison of Six POS Tagging Methods on 12K Sentences Khmer Language POS Tagged Corpus},
  author={Ye Kyaw Thu and Vichet Chea and Yoshinori Sagisaka},
  booktitle={Proceedings of the first Regional Conference on Optical character recognition and Natural language processing technologies for ASEAN languages (ONA 2017)},
  year={2017},
  month={December 7-8},
  address={Phnom Penh, Cambodia}
}


@article{lovenia2024seacrowd,
    title={SEACrowd: A Multilingual Multimodal Data Hub and Benchmark Suite for Southeast Asian Languages}, 
    author={Holy Lovenia and Rahmad Mahendra and Salsabil Maulana Akbar and Lester James V. Miranda and Jennifer Santoso and Elyanah Aco and Akhdan Fadhilah and Jonibek Mansurov and Joseph Marvin Imperial and Onno P. Kampman and Joel Ruben Antony Moniz and Muhammad Ravi Shulthan Habibi and Frederikus Hudi and Railey Montalan and Ryan Ignatius and Joanito Agili Lopo and William Nixon and Börje F. Karlsson and James Jaya and Ryandito Diandaru and Yuze Gao and Patrick Amadeus and Bin Wang and Jan Christian Blaise Cruz and Chenxi Whitehouse and Ivan Halim Parmonangan and Maria Khelli and Wenyu Zhang and Lucky Susanto and Reynard Adha Ryanda and Sonny Lazuardi Hermawan and Dan John Velasco and Muhammad Dehan Al Kautsar and Willy Fitra Hendria and Yasmin Moslem and Noah Flynn and Muhammad Farid Adilazuarda and Haochen Li and Johanes Lee and R. Damanhuri and Shuo Sun and Muhammad Reza Qorib and Amirbek Djanibekov and Wei Qi Leong and Quyet V. Do and Niklas Muennighoff and Tanrada Pansuwan and Ilham Firdausi Putra and Yan Xu and Ngee Chia Tai and Ayu Purwarianti and Sebastian Ruder and William Tjhi and Peerat Limkonchotiwat and Alham Fikri Aji and Sedrick Keh and Genta Indra Winata and Ruochen Zhang and Fajri Koto and Zheng-Xin Yong and Samuel Cahyawijaya},
    year={2024},
    eprint={2406.10118},
    journal={arXiv preprint arXiv: 2406.10118}
}

```