Annotations provide information in addition to the metadata and text of the COVID-19 literature. For example, one may wish to identify and annotate mentions of biomedical or clinical entities, relations or other attributes of interest in the paper text. Annotations can be generated automatically (e.g. using pretrained models for named entity recognition and KB entity linking, with tools such as MetaMap Lite [23] or ScispaCy [59]) or manually through expert annotation (e.g. asking a human to label spans describing population, intervention, comparator and outcome (PICO) elements in clinical trial papers). Several groups have published reusable annotations, either independently or through annotation sharing platforms such as PubTator(https://www.ncbi.nlm.nih.gov/research/pubtator/) or PubAnnotation (http://pubannotation.org/). On PubAnnotation, for example, automatically generated annotations of terms from several ontologies and PICO elements are available for the CORD-19 and LitCovid corpora.