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README.md
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---
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license: cc-by-4.0
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tags:
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- named-entity-recognition
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language:
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- ind
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---
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# indolem_nerui
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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.
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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.
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## Dataset Usage
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Run `pip install nusacrowd` before loading the dataset through HuggingFace's `load_dataset`.
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## Citation
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```
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@INPROCEEDINGS{8275098,
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author={Gultom, Yohanes and Wibowo, Wahyu Catur},
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booktitle={2017 International Workshop on Big Data and Information Security (IWBIS)},
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title={Automatic open domain information extraction from Indonesian text},
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year={2017},
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volume={},
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number={},
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pages={23-30},
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doi={10.1109/IWBIS.2017.8275098}}
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@article{DBLP:journals/corr/abs-2011-00677,
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author = {Fajri Koto and
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Afshin Rahimi and
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Jey Han Lau and
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Timothy Baldwin},
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title = {IndoLEM and IndoBERT: {A} Benchmark Dataset and Pre-trained Language
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Model for Indonesian {NLP}},
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journal = {CoRR},
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volume = {abs/2011.00677},
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year = {2020},
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url = {https://arxiv.org/abs/2011.00677},
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eprinttype = {arXiv},
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eprint = {2011.00677},
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timestamp = {Fri, 06 Nov 2020 15:32:47 +0100},
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biburl = {https://dblp.org/rec/journals/corr/abs-2011-00677.bib},
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bibsource = {dblp computer science bibliography, https://dblp.org}
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}
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```
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## License
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Creative Commons Attribution 4.0
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## Homepage
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[https://indolem.github.io/](https://indolem.github.io/)
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### NusaCatalogue
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For easy indexing and metadata: [https://indonlp.github.io/nusa-catalogue](https://indonlp.github.io/nusa-catalogue)
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