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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.
The coronavirus disease (COVID-19) has claimed the lives of over 350,000 people and infected more than 6 million people worldwide. Several search engines have surfaced to provide researchers with additional tools to find and retrieve information from
We propose a distance supervised relation extraction approach for long-tailed, imbalanced data which is prevalent in real-world settings. Here, the challenge is to learn accurate few-shot models for classes existing at the tail of the class distribut
In this paper, we describe an embedding-based entity recommendation framework for Wikipedia that organizes Wikipedia into a collection of graphs layered on top of each other, learns complementary entity representations from their topology and content
Information Extraction (IE) from the tables present in scientific articles is challenging due to complicated tabular representations and complex embedded text. This paper presents TabLeX, a large-scale benchmark dataset comprising table images genera
Open Information Extraction (OIE) is the task of extracting facts from sentences in the form of relations and their corresponding arguments in schema-free manner. Intrinsic performance of OIE systems is difficult to measure due to the incompleteness