Biomedical NER for the Enterprise with Distillated BERN2 and the Kazu Framework
Wonjin Yoon, Richard Jackson, Elliot Ford, Vladimir Poroshin, Jaewoo Kang · 2022
In order to assist the drug discovery/development process, pharmaceutical companies often apply biomedical NER and linking techniques over internal and public corpora.Decades of study of the field of BioNLP has produced a plethora of algorithms, systems and datasets.However, our experience has been that no single open source system meets all the requirements of a modern pharmaceutical company.In this work, we describe these requirements according to our experience of the industry, and present Kazu, a highly extensible, scalable open source framework designed to support BioNLP for the pharmaceutical sector.Kazu is a built around a computationally efficient version of the BERN2 NER model (TinyBERN2), and subsequently wraps several other BioNLP technologies into one coherent system.