ner-de

Optimized NER for german language with spaCy

Setup Instructions:

• virtualenv venv -p /usr/bin/python3
• source venv/bin/activate
• pip install -r requirements.txt
• python -m spacy download de
• python -m rasa_nlu.train -c configs/spacy_regex_mb_nlu_model_config.json

Training nlu model:

python -m rasa_nlu.train -c configs/spacy_regex_mb_nlu_model_config.json

Cross validate of nlu model:

python -m rasa_nlu.evaluate -d data/nlu_traindata.json -c configs/spacy_regex_mb_nlu_model_config.json --mode crossvalidation

INFO:__main__:CV evaluation (n=10)
INFO:__main__:F1-score: 0.837 (0.052)
INFO:__main__:Precision: 0.914 (0.000)
INFO:__main__:Accuracy: 0.849 (0.044)
INFO:__main__:Finished evaluation

Start nlu as server and test with curl

python -m rasa_nlu.server -c configs/spacy_regex_mb_nlu_model_config.json

curl -XPOST localhost:5000/parse -d '{"q":"Ich bin Tanja Schmitt, geboren am 12.12.2000", "project":"ner-de", "model":"spacy_regex_mb"}'