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A Semantically Enriched Dataset based on Biomedical NER for the COVID19 Open Research Dataset Challenge (2005.08823v1)

Published 18 May 2020 in cs.DL

Abstract: 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.

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Authors (4)
  1. Hermann Kroll (11 papers)
  2. Jan Pirklbauer (5 papers)
  3. Johannes Ruthmann (1 paper)
  4. Wolf-Tilo Balke (16 papers)
Citations (8)

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