Information extraction and data mining in biochemical literature is a
daunting task that demands resource-intensive computation and appropriate means
to scale knowledge ingestion. Being able to leverage this immense source of
technical information helps to drastically reduce costs and time to solution in
multiple application fields from food safety to pharmaceutics. We present a
scalable document ingestion system that integrates data from databases and
publications (in PDF format) in a biochemistry knowledge graph (BCKG). The BCKG
is a comprehensive source of knowledge that can be queried to retrieve known
biochemical facts and to generate novel insights. After describing the
knowledge ingestion framework, we showcase an application of our system in the
field of carbohydrate enzymes. The BCKG represents a way to scale knowledge
ingestion and automatically exploit prior knowledge to accelerate discovery in
biochemical sciences.

我们提出了一种可扩展的文件摄取系统，将数据库和出版物中的数据（以 PDF 格式）集成到生物化学知识图表（BCKG）中。BCKG 是一个全面的知识源，可以查询以检索已知的生物化学事实并生成新的见解。我们展示了我们的系统在碳水化合物酶领域的应用，BCKG 代表了一种自动利用先前知识加速生化科学发现的方法。