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	* Fix scoring on train.py for Chinese
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			@ -174,7 +174,7 @@ def evaluate(Language, gold_tuples, model_dir, gold_preproc=False, verbose=False
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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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            scorer.score(tokens, gold, verbose=verbose)
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            scorer.score(tokens, gold, verbose=verbose, punct_labels=('p', 'punct', 'char'))
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    return scorer
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