code: def lemmatize(self):
          
          for unit in self.unit_list:
              if lemmatizer.lemmatize(unit.text) in self.lemmas:
                      unit.text = lemmatizer.lemmatize(unit.text)
docs: Lemmatize all Units in self.unit_list.
  
          Modifies:
              - self.unit_list: converts the .text property into its lemmatized form.
  
          This method lemmatizes all inflected variants of permissible words to
          those words' respective canonical forms. This is done to ensure that
          each instance of a permissible word will correspond to a term vector with
          which semantic relatedness to other words' term vectors can be computed.
          (Term vectors were derived from a corpus in which inflected words were
          similarly lemmatized, meaning that , e.g., 'dogs' will not have a term
          vector to use for semantic relatedness computation.)