mirror of https://github.com/explosion/spaCy.git
* Train after parsing, not before.
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@ -164,8 +164,8 @@ def evaluate(Language, gold_tuples, model_dir, gold_preproc=False, verbose=False
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if raw_text is None:
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tokens = nlp.tokenizer.tokens_from_list(annot_tuples[1])
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nlp.tagger(tokens)
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nlp.entity(tokens)
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nlp.parser(tokens)
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nlp.entity(tokens)
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else:
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tokens = nlp(raw_text)
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gold = GoldParse(tokens, annot_tuples)
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