We use pretrained BERT (Devlin et al., 2019), 12 fine-tuned on the training splits of the datasets from which our test data was drawn.
we fine-tune BERT five times, once on each dataset, and then test each model on the subset of our re-annotated p/h pairs that were drawn from the dataset on which it was fine-tuned.