README.md

---
language: 
- ind
pretty_name: Indolem Ner Ugm
task_categories: 
- named-entity-recognition
tags: 
- named-entity-recognition
---

NER UGM is a Named Entity Recognition dataset that comprises 2,343 sentences from news articles, and was constructed at the University of Gajah Mada based on five named entity classes: person, organization, location, time, and quantity.


## Languages

ind

## Supported Tasks

Named Entity Recognition

## Dataset Usage
### Using `datasets` library
```
from datasets import load_dataset
dset = datasets.load_dataset("SEACrowd/indolem_ner_ugm", trust_remote_code=True)
```
### Using `seacrowd` library
```import seacrowd as sc
# Load the dataset using the default config
dset = sc.load_dataset("indolem_ner_ugm", schema="seacrowd")
# Check all available subsets (config names) of the dataset
print(sc.available_config_names("indolem_ner_ugm"))
# 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://indolem.github.io/](https://indolem.github.io/)

## Dataset Version

Source: 1.0.0. SEACrowd: 2024.06.20.

## Dataset License

Creative Commons Attribution 4.0

## Citation

If you are using the **Indolem Ner Ugm** dataloader in your work, please cite the following:
```
@inproceedings{koto-etal-2020-indolem,
    title = "{I}ndo{LEM} and {I}ndo{BERT}: A Benchmark Dataset and Pre-trained Language Model for {I}ndonesian {NLP}",
    author = "Koto, Fajri  and
      Rahimi, Afshin  and
      Lau, Jey Han  and
      Baldwin, Timothy",
    booktitle = "Proceedings of the 28th International Conference on Computational Linguistics",
    month = dec,
    year = "2020",
    address = "Barcelona, Spain (Online)",
    publisher = "International Committee on Computational Linguistics",
    url = "https://aclanthology.org/2020.coling-main.66",
    doi = "10.18653/v1/2020.coling-main.66",
    pages = "757--770"
}
@phdthesis{fachri2014pengenalan,
  title     = {Pengenalan Entitas Bernama Pada Teks Bahasa Indonesia Menggunakan Hidden Markov Model},
  author    = {FACHRI, MUHAMMAD},
  year      = {2014},
  school    = {Universitas Gadjah Mada}
}


@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}
}

```