class_docstr: A ``WordSplitter`` splits strings into words.  This is typically called a "tokenizer" in NLP,
  because splitting strings into characters is trivial, but we use ``Tokenizer`` to refer to the
  higher-level object that splits strings into tokens (which could just be character tokens).
  So, we're using "word splitter" here for this.
class_docstr_tok: ["A","``","WordSplitter","``","splits","strings","into","words",".","This","is","typically","called","a","``","tokenizer","''","in","NLP",",","because","splitting","strings","into","characters","is","trivial",",","but","we","use","``","Tokenizer","``","to","refer","to","the","higher-level","object","that","splits","strings","into","tokens","(","which","could","just","be","character","tokens",")",".","So",",","we","'re","using","``","word","splitter","''","here","for","this","."]
docstr: Splits ``sentence`` into a list of :class:`Token` objects.
docstr_tok: ["Splits","``","sentence","``","into","a","list","of",":","class",":","`","Token","`","objects","."]
code: def split_words(self, sentence):
      """
      Splits ``sentence`` into a list of :class:`Token` objects.
      """
      raise NotImplementedError
  
imports: from __future__ import absolute_import
  import re
  import spacy
  from allennlp.common import Registrable
  from allennlp.common.util import get_spacy_model
  from allennlp.data.tokenizers.token import Token
label_desc: Use image node_id 2 for calling the WordSplitter obj's underlying member method code with example usage: obj.split_words(sentence) without return types