      else:
          file_ = loc.open()
      probs = {}
      for line in file_:
          freq, doc_freq, key = line.split('\t', 2)
          doc_freq = int(doc_freq)
          freq = int(freq)
          if doc_freq >= min_doc_freq and freq >= min_freq and len(key) < max_length:
  #            word = literal_eval(key)
              word = key
 
</s> remove         freq, doc_freq, key = line.split('\t', 2)
 </s> add         freq, doc_freq, key = line.rstrip().split('\t', 2) </s> remove    
    FLAG14 = 14
    FLAG15
    FLAG16
    FLAG17
    FLAG18
 </s> add     IS_BRACKET
    IS_QUOTE
    IS_LEFT_PUNCT
    IS_RIGHT_PUNCT

    FLAG18 = 18 </s> remove # Move these up to FLAG14--FLAG18 once we finish the functionality and
# are ready to regenerate the model
#IS_BRACKET
#IS_QUOTE
#IS_LEFT_PUNCT
#IS_RIGHT_PUNCT
 </s> add  </s> remove     'spacy.symbols']
 </s> add     'spacy.symbols',
    'spacy.en.iterators',
    'spacy.de.iterators']
        freq, doc_freq, key = line.rstrip().split('\t', 2)
      else:
          file_ = loc.open()
      probs = {}
      for line in file_:
        freq, doc_freq, key = line.rstrip().split('\t', 2)
          doc_freq = int(doc_freq)
          freq = int(freq)
          if doc_freq >= min_doc_freq and freq >= min_freq and len(key) < max_length:
  #            word = literal_eval(key)
              word = key
keep keep keep keep replace keep keep keep keep keep
 introduce lang field for LexemeC to hold language id
put noun_chunk logic into iterators.py for each language separately 
bin/init_model.py