CODA-19 is a human-annotated dataset that denotes the Background, Purpose, Method, Finding/Contribution, and Other for 10,966 English abstracts in the COVID-19 Open Research Dataset.

CODA-19 was created by 248 crowd workers from Amazon Mechanical Turk collectively within ten days. Each abstract was annotated by nine different workers, and the final labels were obtained by majority voting.

CODA-19's labels have an accuracy of 82% and an inter-annotator agreement (Cohen's kappa) of 0.74 when compared against expert labels on 129 abstracts.