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* Raise exception on non-projective input
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@ -130,8 +130,13 @@ def train(Language, gold_tuples, model_dir, n_iter=15, feat_set=u'basic',
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raw_text = add_noise(raw_text, corruption_level)
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tokens = nlp.tokenizer(raw_text)
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nlp.tagger(tokens)
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gold = GoldParse(tokens, annot_tuples, make_projective=True)
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loss += nlp.parser.train(tokens, gold)
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gold = GoldParse(tokens, annot_tuples, make_projective=False)
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if not gold.is_projective:
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raise Exception(
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"Non-projective sentence in training, after we should "
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"have enforced projectivity: %s" % annot_tuples
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)
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loss += nlp.parser.train(tokens, gold)
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nlp.entity.train(tokens, gold)
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nlp.tagger.train(tokens, gold.tags)
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