Bringing IBM NLP capabilities to the CORD-19 Dataset

To assist in the fight against the COVID-19 pandemic, prominent research institutes led by Allen Institute for AI (AI2) released earlier this year the COVID-19 Open Research Dataset (CORD-19). Comprised of scientific articles related to COVID-19, Sars-Cov-2, and related coronaviruses, the dataset (which at the time of writing this contains more than 75,000 full text scientific papers) is intended to mobilize researchers to apply recent advances in natural language processing to generate new insights in support of the fight against this infectious disease (1,2). While a tremendous resource, the dataset initially did not include information found in tables due to the difficulty of extracting tabular data. However, following the launch of the Kaggle challenge associated with CORD-19, table information rose to become the most requested feature by challenge participants. Recognizing that critical scientific facts and data are often organized in a tabular format, IBM Research AI offered to apply our extensive experience in document and table conversion to update the CORD-19 dataset and, in turn, open up additional critical information to the global science and medical community in efforts to fight COVID-19.