Solving NER with BERT for any entity type with very little training data (compared to past approaches)

One of the roadblocks to entity recognition for any entity type other than person, location, organization, disease, gene, drugs, and species is the absence of labeled training data.

BERT offers a solution that works in practice for entity recognition of a custom type with very little labeled data — sometimes even about 300 examples of labeled data may suffice to get a first cut working solution.