class_docstr: Attributes:
      text (str, optional): token text
      lemma (str, optional): token lemma
      pos (str, optional): token pos
      ner (str, optional): token ner
      idx (int, optional): token start index (within the sentence)
class_docstr_tok: ["Attributes",":","text","(","str",",","optional",")",":","token","text","lemma","(","str",",","optional",")",":","token","lemma","pos","(","str",",","optional",")",":","token","pos","ner","(","str",",","optional",")",":","token","ner","idx","(","int",",","optional",")",":","token","start","index","(","within","the","sentence",")"]
code: def __init__(
      self, text=None, lemma=None, pos=None, ner=None, idx=None
  ):
      self.text = text
      self.lemma = lemma
      self.pos = pos
      self.ner = ner
      self.idx = idx
      self.dep_rel_list = []
      self.gov = None
  
imports: import csv
  from enum import Enum
  from os import PathLike
  from nlp_architect.models.absa import TRAIN_LEXICONS
label_desc: Use image node_id 1 to create a new DepRelationTerm object from inherited base classes: object with example: obj = DepRelationTerm(text, lemma, pos, ner, idx)