This model repository presents the NER module used in the initial release of the KAZU (Korea University and AstraZeneca) framework.
* For the framework, please visit https://github.com/AstraZeneca/KAZU
* For demo, please visit http://kazu.korea.ac.kr
* For details about the model, please see our paper entitled **Biomedical NER for the Enterprise with Distillated BERN2 and the Kazu Framework**, (EMNLP 2022 industry track).
* (For research purposes:) The training and evaluation code for multi-label token classification, which we used when training this model, is available at https://github.com/dmis-lab/KAZU-NER-module


More details to be announced soon.


### Citation info
Joint-first authorship of **Richard Jackson** (AstraZeneca) and **WonJin Yoon** (Korea University).
<br>Please cite the paper using the simplified citation format provided in the following section, or find the [full citation information here](https://aclanthology.org/2022.emnlp-industry.63.bib)
```
@inproceedings{YoonAndJackson2022BiomedicalNER,
  title="Biomedical {NER} for the Enterprise with Distillated {BERN}2 and the Kazu Framework",
  author="Yoon, Wonjin and Jackson, Richard and Ford, Elliot and Poroshin, Vladimir and Kang, Jaewoo",
  booktitle="Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: Industry Track",
  month = dec,
  year = "2022",    
  address = "Abu Dhabi, UAE",
  publisher = "Association for Computational Linguistics",
  url = "https://aclanthology.org/2022.emnlp-industry.63",
  pages = "619--626",
}
```


### Contact Information
For help or issues using the codes or model (NER module of KAZU) in this repository, please contact WonJin Yoon (wonjin.info (at) gmail.com) or submit a GitHub issue.