> Overall, there's no open-source high accuracy NER model that you can use out-of-a-box"
Part of it is most underestimate the complexity of NER and the rest of it, in my opinion, is that NER is not well-defined as a classification problem.
At least in my experience, having a specific battery of questions to query documents, first by transformer based semantic search and narrowed by Q/A models, removed the need for explicit NER, entity linking or relation extraction. For the case of entities as features for rule systems, shallow models and using all label predictions instead of just selecting argmax has been sufficiently robust. Using big transformers for classification doesn't pay enough to be worth it there.
Part of it is most underestimate the complexity of NER and the rest of it, in my opinion, is that NER is not well-defined as a classification problem.
At least in my experience, having a specific battery of questions to query documents, first by transformer based semantic search and narrowed by Q/A models, removed the need for explicit NER, entity linking or relation extraction. For the case of entities as features for rule systems, shallow models and using all label predictions instead of just selecting argmax has been sufficiently robust. Using big transformers for classification doesn't pay enough to be worth it there.