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A Semantically Enriched Dataset based on Biomedical NER for the COVID19 Open Research Dataset Challenge

Research into COVID-19 is a big challenge and highly relevant at the moment. New tools are required to assist medical experts in their research with relevant and valuable information. The COVID-19 Open Research Dataset Challenge (CORD-19) is a "call to action" for computer scientists to develop these innovative tools. Many of these applications are empowered by entity information, i. e. knowing which entities are used within a sentence. For this paper, we have developed a pipeline upon the latest Named Entity Recognition tools for Chemicals, Diseases, Genes and Species. We apply our pipeline to the COVID-19 research challenge and share the resulting entity mentions with the community.

preprint2020arXivOpen access
Hermann KrollJan PirklbauerJohannes RuthmannWolf-Tilo Balke
Digital Libraries
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Open access4 authors1 topic
Imported metadata coverageMissing code, dataset, citation and institution fields are tracked without dominating the paper.Details
Citations: 0Reviews: 0Saves: 0Code: not linkedDataset: not linkedInstitutions: 0

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Hermann KrollJan PirklbauerJohannes RuthmannWolf-Tilo Balke

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