| 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. | |