code: def is_base_form(self, token: Token) -> bool:
      """
      Check whether we're dealing with an uninflected paradigm, so we can
      avoid lemmatization entirely.
  
      univ_pos (str / int): The token's universal part-of-speech tag.
      morphology (dict): The token's morphological features following the
          Universal Dependencies scheme.
      """
      univ_pos = token.pos_.lower()
      morphology = token.morph.to_dict()
      if univ_pos == "noun" and morphology.get("Number") == "Sing":
          return True
      elif univ_pos == "verb" and morphology.get("VerbForm") == "Inf":
          return True
      # This maps 'VBP' to base form -- probably just need 'IS_BASE'
      # morphology
      elif univ_pos == "verb" and (
          morphology.get("VerbForm") == "Fin"
          and morphology.get("Tense") == "Pres"
          and morphology.get("Number") is None
      ):
          return True
      elif univ_pos == "adj" and morphology.get("Degree") == "Pos":
          return True
      elif morphology.get("VerbForm") == "Inf":
          return True
      elif morphology.get("VerbForm") == "None":
          return True
      elif morphology.get("Degree") == "Pos":
          return True
      else:
          return False
  
imports: from ...pipeline import Lemmatizer
  from ...tokens import Token
label_desc: Use image node_id 1 for calling the EnglishLemmatizer obj's underlying member method code with example usage: obj.is_base_form(token) and returns: True, True, True, True, True, True, True, False