4 Language NER in Flair (English, German, Dutch and Spanish) This is the fast 4 class NER model for 4 CoNLL 03 languages that ships with Flair. Also kind of works for related languages like French. F1 Score: 91,51 (CoNLL 03 English), 85,72 (CoNLL 03 German revised), 86,22 (CoNLL 03 Dutch), 85,78 (CoNLL 03 Spanish) Predicts 4 tags: tag meaning PER person name LOC location name ORG organization name MISC other name Based on Flair embeddings and LSTM CRF. Demo: How to use in Flair Requires: Flair ( pip install flair ) This yields the following output: So, the entities " George Washington " (labeled as a person ) and " Washington " (labeled as a location ) are found in the sentence " George Washington ging nach Washington ". Training: Script to train this model The following Flair script was used to train this model: Cite Please cite the following papers when using this model.
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