论文标题
基于CoVID19开放研究数据集挑战的基于生物医学NER的语义丰富数据集
A Semantically Enriched Dataset based on Biomedical NER for the COVID19 Open Research Dataset Challenge
论文作者
论文摘要
目前，对Covid-19的研究是一个巨大的挑战，并且高度相关。需要新工具来帮助医学专家提供相关和有价值的信息。 COVID-19开放研究数据集挑战（CORD-19）是计算机科学家开发这些创新工具的“行动呼吁”。这些应用中的许多应用程序都由实体信息授权，即。 e。知道句子中使用了哪些实体。对于本文，我们已经开发了有关化学，疾病，基因和物种的最新命名实体识别工具的管道。我们将管道应用于Covid-19研究挑战赛，并与社区分享所得的实体提及。
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.
