                  else:
                      self.words[i] = words[gold_i]
                      self.tags[i] = tags[gold_i]
                      self.morphs[i] = morphs[gold_i]
                      self.lemmas[i] = lemmas[gold_i]
                      self.sent_starts[i] = sent_starts[gold_i]
                      if heads[gold_i] is None:
 
</s> remove                     self.morphs[i] = set()
                    self.lemmas[i] = None
 </s> add  </s> remove             self.morphs = [None] * len(doc)
            self.lemmas = [None] * len(doc)
 </s> add 
                    self.pos[i] = pos[gold_i]
                  else:
                      self.words[i] = words[gold_i]
                      self.tags[i] = tags[gold_i]
                    self.pos[i] = pos[gold_i]
                      self.morphs[i] = morphs[gold_i]
                      self.lemmas[i] = lemmas[gold_i]
                      self.sent_starts[i] = sent_starts[gold_i]
                      if heads[gold_i] is None:
keep keep add keep keep keep keep
 Add support for pos/morphs/lemmas in training data (#4941)

Add support for pos/morphs/lemmas throughout `GoldParse`, `Example`, and
`docs_to_json()`. 
spacy/gold.pyx