Anecdotally, I got better NER results with spaCY than OpenNLP and CoreNLP with their respective default models, and spaCY was easier to install (though I'm biased, being more familiar with Python tooling and documentation style). I was eventually implementing in Java so I did use OpenNLP for sentence splitting, but I retrained the NER with data bootstrapped from spaCY, in a way similar to what the Prodigy tool is aiming to facilitate, by first classifying using the default/vanilla model and then manually correcting labels where they were incorrect.