code: def __init__(
      self,
      n_jobs=4,
      embed_path=PACKAGE_DIRECTORY + "/weights/",
      gold_mentions=False,
      blacklist=False,
  ):
      self.n_jobs = n_jobs
      self.features = {}
      self.utts_text = []
      self.utts_tokens = []
      self.utts_corefs = []
      self.utts_speakers = []
      self.utts_doc_idx = []
      self.docs_names = []
      self.docs = []
      if embed_path is not None:
          self.embed_extractor = EmbeddingExtractor(embed_path)
      self.trainable_embed = []
      self.trainable_voc = []
      self.gold_mentions = gold_mentions
      self.blacklist = blacklist
  
imports: import re
  import argparse
  import time
  import os
  import io
  import pickle
  import spacy
  import numpy
  from tqdm import tqdm
  from neuralcoref.train.compat import unicode_
  from neuralcoref.train.document import Mention, Document, Speaker, EmbeddingExtractor, MISSING_WORD, extract_mentions_spans
  from neuralcoref.train.utils import parallel_process
label_desc: Use image node_id 1 to create a new ConllCorpus object from inherited base classes: object with example: obj = ConllCorpus(n_jobs, embed_path, gold_mentions, blacklist)