BERT is effective across domains, providing between 25% and 55% error reduction over the base neural parsers.
as for word embeddings, the pre-trained BERT representations do not generally provide a larger error reduction in out-of-domain settings than in in-domain (although a possible confound is that the BERT model is fine-tuned on the relatively small amount of in-domain treebank data, along with the other parser parameters).