We evaluate zero-shot transfer performance by training on one dataset and evaluating on another, without any retraining.
we consider three zero-shot transfer scenarios: training with Universal POS Tags on the Penn Treebank and then predicting the standard, fine-grained POS tags, training on the CoNLL 2003 NER data and predicting on the fine-grained OntoNotes NER data (Hovy et al., 2006) using the setup of Strubell et al.