class_docstr: Sencence in CoNLL-X format.
  
  Args:
      transform (CoNLL):
          A :class:`CoNLL` object.
      lines (list[str]):
          A list of strings composing a sentence in CoNLL-X format.
          Comments and non-integer IDs are permitted.
  
  Examples:
      >>> lines = ['# text = But I found the location wonderful and the neighbors very kind.',
                   '1\tBut\t_\t_\t_\t_\t_\t_\t_\t_',
                   '2\tI\t_\t_\t_\t_\t_\t_\t_\t_',
                   '3\tfound\t_\t_\t_\t_\t_\t_\t_\t_',
                   '4\tthe\t_\t_\t_\t_\t_\t_\t_\t_',
                   '5\tlocation\t_\t_\t_\t_\t_\t_\t_\t_',
                   '6\twonderful\t_\t_\t_\t_\t_\t_\t_\t_',
                   '7\tand\t_\t_\t_\t_\t_\t_\t_\t_',
                   '7.1\tfound\t_\t_\t_\t_\t_\t_\t_\t_',
                   '8\tthe\t_\t_\t_\t_\t_\t_\t_\t_',
                   '9\tneighbors\t_\t_\t_\t_\t_\t_\t_\t_',
                   '10\tvery\t_\t_\t_\t_\t_\t_\t_\t_',
                   '11\tkind\t_\t_\t_\t_\t_\t_\t_\t_',
                   '12\t.\t_\t_\t_\t_\t_\t_\t_\t_']
      >>> sentence = CoNLLSentence(transform, lines)  # fields in transform are built from ptb.
      >>> sentence.arcs = [3, 3, 0, 5, 6, 3, 6, 9, 11, 11, 6, 3]
      >>> sentence.rels = ['cc', 'nsubj', 'root', 'det', 'nsubj', 'xcomp',
                           'cc', 'det', 'dep', 'advmod', 'conj', 'punct']
      >>> sentence
      # text = But I found the location wonderful and the neighbors very kind.
      1       But     _       _       _       _       3       cc      _       _
      2       I       _       _       _       _       3       nsubj   _       _
      3       found   _       _       _       _       0       root    _       _
      4       the     _       _       _       _       5       det     _       _
      5       location        _       _       _       _       6       nsubj   _       _
      6       wonderful       _       _       _       _       3       xcomp   _       _
      7       and     _       _       _       _       6       cc      _       _
      7.1     found   _       _       _       _       _       _       _       _
      8       the     _       _       _       _       9       det     _       _
      9       neighbors       _       _       _       _       11      dep     _       _
      10      very    _       _       _       _       11      advmod  _       _
      11      kind    _       _       _       _       6       conj    _       _
      12      .       _       _       _       _       3       punct   _       _
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code: def __init__(self, transform, lines):
      super().__init__(transform)
  
      self.values = []
      # record annotations for post-recovery
      self.annotations = dict()
  
      for i, line in enumerate(lines):
          value = line.split("\t")
          if value[0].startswith("#") or not value[0].isdigit():
              self.annotations[-i - 1] = line
          else:
              self.annotations[len(self.values)] = line
              self.values.append(value)
      self.values = list(zip(*self.values))
  
imports: from collections.abc import Iterable
  import nltk
  from tqdm import tqdm
  from underthesea.utils.sp_parallel import is_master
label_desc: Use image node_id 1 to create a new CoNLLSentence object from inherited base classes: Sentence with example: obj = CoNLLSentence(transform, lines)