Before revision:  We measure the impact of combining large numbers of ontologies and present a case study on rapidly building classifiers for COVID-19 clinical tasks. Our framework demonstrates how a wide range of medical entity classifiers can be quickly constructed using weak supervision and without requiring manually-labeled training data .
After revision:  We measure the impact of combining large numbers of ontologies and present a case study on rapidly building classifiers for COVID-19 presenting symptoms and risk factors .