class_docstr: A mention (possible anaphor) inherite from spacy Span class with additional informations
docstr: Arguments:
      span (spaCy Span): the spaCy span from which creating the Mention object
      mention_index (int): index of the Mention in the Document
      utterance_index (int): index of the utterance of the Mention in the Document
      utterances_start_sent (int): index of the first sentence of the utterance of the Mention in the Document
          (an utterance can comprise several sentences)
      speaker (Speaker): the speaker of the mention
      gold_label (anything): a gold label associated to the Mention (for training)
docstr_tok: ["Arguments",":","span","(","spaCy","Span",")",":","the","spaCy","span","from","which","creating","the","Mention","object","mention_index","(","int",")",":","index","of","the","Mention","in","the","Document","utterance_index","(","int",")",":","index","of","the","utterance","of","the","Mention","in","the","Document","utterances_start_sent","(","int",")",":","index","of","the","first","sentence","of","the","utterance","of","the","Mention","in","the","Document","(","an","utterance","can","comprise","several","sentences",")","speaker","(","Speaker",")",":","the","speaker","of","the","mention","gold_label","(","anything",")",":","a","gold","label","associated","to","the","Mention","(","for","training",")"]
code: def __init__(
      self,
      span,
      mention_index,
      utterance_index,
      utterances_start_sent,
      speaker=None,
      gold_label=None,
  ):
      """
      Arguments:
          span (spaCy Span): the spaCy span from which creating the Mention object
          mention_index (int): index of the Mention in the Document
          utterance_index (int): index of the utterance of the Mention in the Document
          utterances_start_sent (int): index of the first sentence of the utterance of the Mention in the Document
              (an utterance can comprise several sentences)
          speaker (Speaker): the speaker of the mention
          gold_label (anything): a gold label associated to the Mention (for training)
      """
      self.index = mention_index
      self.utterance_index = utterance_index
      self.utterances_sent = (
          utterances_start_sent + self._get_doc_sent_number()
      )
      self.speaker = speaker
      self.gold_label = gold_label
      self.spans_embeddings = None
      self.words_embeddings = None
      self.features = None
  
      self.features_ = None
      self.spans_embeddings_ = None
      self.words_embeddings_ = None
  
      self.mention_type = self._get_type()
      self.propers = set(self.content_words)
      self.entity_label = self._get_entity_label()
      self.in_entities = self._get_in_entities()
  
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 to create a new Mention object from inherited base classes: spacy.tokens with example: obj = Mention(span, mention_index, utterance_index, utterances_start_sent, speaker, gold_label)