code: def stem(string, language, resources):
      from snips_nlu_utils import normalize
  
      normalized_string = normalize(string)
      tokens = tokenize_light(normalized_string, language)
      stemmed_tokens = [_stem(token, resources) for token in tokens]
      return " ".join(stemmed_tokens)
  
file_path: snips-nlu/snips_nlu/preprocessing.py
imports: from __future__ import unicode_literals
  from builtins import object
  from snips_nlu.resources import get_stems
label_desc: Use image node_id 1 for calling a global function with example usage: stem(string, language, resources) and returns: str