Named Entity recognition annotator allows for a generic model to be trained by utilizing a deep learning algorithm (Char CNNs - BiLSTM - CRF - word embeddings) inspired on a former state of the art model for NER: Chiu & Nicols, Named Entity Recognition with Bidirectional LSTM,CNN. Pretrained named entity recognition deep learning model for Drugs.
DrugChem (Drug and Chemicals)
How to use
model = NerDLModel.pretrained("ner_drugs","en","clinical/models")\ .setInputCols("sentence","token","word_embeddings")\ .setOutputCol("ner")
val model = NerDLModel.pretrained("ner_drugs","en","clinical/models") .setInputCols("sentence","token","word_embeddings") .setOutputCol("ner")
|Compatibility:||Spark NLP 2.4.4+|
|Input labels:||[sentence, token, word_embeddings]|
Trained on i2b2_med7 + FDA with