          Parser.add_label(self, label)
          if isinstance(label, basestring):
              label = self.vocab.strings[label]
          for attr, freqs in self.vocab.serializer_freqs:
              if attr == ENT_TYPE and label not in freqs:
                  freqs.append([label, 1])
          self.vocab._serializer = None
 
</s>
        # Set label into serializer. Super hacky :(
          Parser.add_label(self, label)
          if isinstance(label, basestring):
              label = self.vocab.strings[label]
        # Set label into serializer. Super hacky :(
          for attr, freqs in self.vocab.serializer_freqs:
              if attr == ENT_TYPE and label not in freqs:
                  freqs.append([label, 1])
          self.vocab._serializer = None
keep keep add keep keep keep keep
 WIP on add_label bug during NER training

Currently when a new label is introduced to NER during training,
it causes the labels to be read in in an unexpected order. This
invalidates the model.
spacy/pipeline.pyx