class_docstr: Main data class: encapsulate list of utterances, mentions and speakers
  Process utterances to extract mentions and pre-compute mentions features
code: def set_genre(self, conll):
      if conll is not None:
          genre = np.zeros((7,))
          genre[conll] = 1
      else:
          genre = np.array(0, ndmin=1, copy=False)
      return conll, genre
  
imports: import re
  import io
  from six import string_types, integer_types
  from spacy.tokens import Span, Token
  from neuralcoref.train.compat import unicode_
  from neuralcoref.train.utils import encode_distance, parallel_process
  import spacy
  import numpy
label_desc: Use image node_id 2 for calling the Document obj's underlying member method code with example usage: obj.set_genre(conll) and returns: conll,  genre