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* Skip sentences of length 1 in training
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@ -178,6 +178,8 @@ def train(Language, gold_tuples, model_dir, n_iter=15, feat_set=u'basic',
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else:
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sents = _merge_sents(sents)
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for annot_tuples, ctnt in sents:
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if len(annot_tuples[1]) == 1:
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continue
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score_model(scorer, nlp, raw_text, annot_tuples, train_tags)
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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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