original_docstring: 
          Get NLP object with NER pipe enabled
  
          :return: NLP object
          
docstring: Get NLP object with NER pipe enabled
docstring_tokens: Get NLP object with NER pipe enabled
code: def create_nlp(self):
          """
          Get NLP object with NER pipe enabled
  
          :return: NLP object
          """
  
          # parse path and ensure exists
          self.storage.nlp_path = self.resolve_ensure_path(file_path=self.storage.config.nlp_name)
  
          try:
              if self.storage.nlp_obj:
                  nlp = self.storage.nlp_obj
              else:
                  # load NLP object with custom path to be loaded first, if fails, get the base which is lang code from spaCy.
                  nlp = spacy.load(name=self.storage.nlp_path)
          except IOError:
              if not self.storage.config.nlp_base:
                  self.storage.config.nlp_base = 'en_core_web_sm'
              nlp = spacy.load(name=self.storage.config.nlp_base)
          return nlp
code_tokens: def create_nlp ( self ) : self . storage . nlp_path = self . resolve_ensure_path ( file_path = self . storage . config . nlp_name ) try : if self . storage . nlp_obj : nlp = self . storage . nlp_obj else : nlp = spacy . load ( name = self . storage . nlp_path ) except IOError : if not self . storage . config . nlp_base : self . storage . config . nlp_base = 'en_core_web_sm' nlp = spacy . load ( name = self . storage . config . nlp_base ) return nlp
short_docstring: Get NLP object with NER pipe enabled
short_docstring_tokens: Get NLP object with NER pipe enabled
comment: """
          Get NLP object with NER pipe enabled
  
          :return: NLP object
          """$SEP$# parse path and ensure exists$SEP$# load NLP object with custom path to be loaded first, if fails, get the base which is lang code from spaCy.