dmis-lab / KAZU-NER-module-distil-v1.0

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).
Please cite the paper using the simplified citation format provided in the following section, or find the full citation information here

@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.