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Use create_pipe instead of importing the entity recognizer

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ines 2017-10-26 15:15:26 +02:00
parent d425ede7e9
commit 586b9047fd
1 changed files with 6 additions and 3 deletions
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9
examples/training/train_new_entity_type.py
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@ -34,7 +34,6 @@ from pathlib import Path
import spacy import spacy
from spacy.gold import GoldParse, minibatch from spacy.gold import GoldParse, minibatch
from spacy.pipeline import NeuralEntityRecognizer
# new entity label # new entity label
@ -77,10 +76,14 @@ def main(model=None, new_model_name='animal', output_dir=None):
print("Created blank 'en' model") print("Created blank 'en' model")
# Add entity recognizer to model if it's not in the pipeline # Add entity recognizer to model if it's not in the pipeline
# nlp.create_pipe works for built-ins that are registered with spaCy
if 'ner' not in nlp.pipe_names: if 'ner' not in nlp.pipe_names:
nlp.add_pipe(NeuralEntityRecognizer(nlp.vocab)) ner = nlp.create_pipe('ner')
nlp.add_pipe(ner)
# otherwise, get it, so we can add labels to it
else:
ner = nlp.get_pipe('ner')
ner = nlp.get_pipe('ner') # get entity recognizer
ner.add_label(LABEL) # add new entity label to entity recognizer ner.add_label(LABEL) # add new entity label to entity recognizer
# get names of other pipes to disable them during training # get names of other pipes to disable them during training