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This model repository presents the NER module used in the initial release of the KAZU (Korea University and AstraZeneca) framework. |
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* For the framework, please visit https://github.com/AstraZeneca/KAZU |
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* For demo, please visit http://kazu.korea.ac.kr |
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* 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). |
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* (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 |
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More details to be announced soon. |
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### Citation info |
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Joint-first authorship of **Richard Jackson** (AstraZeneca) and **WonJin Yoon** (Korea University). |
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<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) |
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``` |
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@inproceedings{YoonAndJackson2022BiomedicalNER, |
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title="Biomedical {NER} for the Enterprise with Distillated {BERN}2 and the Kazu Framework", |
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author="Yoon, Wonjin and Jackson, Richard and Ford, Elliot and Poroshin, Vladimir and Kang, Jaewoo", |
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booktitle="Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: Industry Track", |
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month = dec, |
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year = "2022", |
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address = "Abu Dhabi, UAE", |
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publisher = "Association for Computational Linguistics", |
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url = "https://aclanthology.org/2022.emnlp-industry.63", |
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pages = "619--626", |
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} |
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``` |
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### Contact Information |
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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. |
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