anchor.diff:              {
                   ORTH: u'me'}])
       assert [w.text for w in nlp(u'gimme that')] == [u'gim', u'me', u'that']
  -    assert [w.lemma_ for w in nlp(u'gimme that')] == [u'give', u'-PRON-', u'that']
  +    assert [w.lemma_ for w in nlp(u'gimme that')] == [u'give', u'me', u'that']
   
   p
       |  The special case doesn't have to match an entire whitespace-delimited
  
positive.code:     |  The special case rules have precedence over the punctuation splitting:
  
  +code.
      nlp.tokenizer.add_special_case(u"...gimme...?",
          [{
              ORTH: u'...gimme...?", LEMMA: "give", TAG: "VB"}])
      assert len(nlp(u'...gimme...?')) == 1
  
  p
  
negative.code:     |  #[+api("tokenizer") #[code Tokenizer]] instance:
  
  +code.
      import spacy
      from spacy.symbols import ORTH, LEMMA, POS
  
      nlp = spacy.load('en')
      assert [w.text for w in nlp(u'gimme that')] == [u'gimme', u'that']
      nlp.tokenizer.add_special_case(u'gimme',
  