code: def capitalize(text, language, resources):
      tokens = tokenize_light(text, language)
      stop_words = get_stop_words(resources)
      return get_default_sep(language).join(
          t.title() if t.lower() not in stop_words else t.lower()
          for t in tokens
      )
  
file_path: snips-nlu/snips_nlu/data_augmentation.py
imports: from __future__ import unicode_literals
  from builtins import next
  from copy import deepcopy
  from itertools import cycle
  from future.utils import iteritems
  from snips_nlu.constants import CAPITALIZE, DATA, ENTITIES, ENTITY, INTENTS, TEXT, UTTERANCES
  from snips_nlu.entity_parser.builtin_entity_parser import is_builtin_entity
  from snips_nlu.languages import get_default_sep
  from snips_nlu.preprocessing import tokenize_light
  from snips_nlu.resources import get_stop_words
label_desc: Use image node_id 1 for calling a global function with example usage: capitalize(text, language, resources) and returns: get_default_sep