SEACrowd/indolem_nerui

NER UI is a Named Entity Recognition dataset that contains 2,125 sentences obtained via an annotation assignment in an NLP course at the University of Indonesia in 2016. The corpus has three named entity classes: location, organisation, and person with training/dev/test distribution: 1,530/170/42 and based on 5-fold cross validation.

Languages

ind

Supported Tasks

Named Entity Recognition

Dataset Usage

Using datasets library

from datasets import load_dataset
dset = datasets.load_dataset("SEACrowd/indolem_nerui", trust_remote_code=True)

Using seacrowd library

# Load the dataset using the default config
dset = sc.load_dataset("indolem_nerui", schema="seacrowd")
# Check all available subsets (config names) of the dataset
print(sc.available_config_names("indolem_nerui"))
# 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.

Dataset Homepage

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 Nerui dataloader in your work, please cite the following:

@INPROCEEDINGS{8275098,
  author={Gultom, Yohanes and Wibowo, Wahyu Catur},
  booktitle={2017 International Workshop on Big Data and Information Security (IWBIS)},
  title={Automatic open domain information extraction from Indonesian text},
  year={2017},
  volume={},
  number={},
  pages={23-30},
  doi={10.1109/IWBIS.2017.8275098}}

@article{DBLP:journals/corr/abs-2011-00677,
  author    = {Fajri Koto and
               Afshin Rahimi and
               Jey Han Lau and
               Timothy Baldwin},
  title     = {IndoLEM and IndoBERT: {A} Benchmark Dataset and Pre-trained Language
               Model for Indonesian {NLP}},
  journal   = {CoRR},
  volume    = {abs/2011.00677},
  year      = {2020},
  url       = {https://arxiv.org/abs/2011.00677},
  eprinttype = {arXiv},
  eprint    = {2011.00677},
  timestamp = {Fri, 06 Nov 2020 15:32:47 +0100},
  biburl    = {https://dblp.org/rec/journals/corr/abs-2011-00677.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}


@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}
}