                  if doc[i].text.isspace():
                      self.words[i] = doc[i].text
                      self.tags[i] = "_SP"
                      self.heads[i] = None
                      self.labels[i] = None
                      self.ner[i] = None
                      self.sent_starts[i] = 0
                  if gold_i is None:
                      if i in i2j_multi:
 
</s> remove                     self.morphs[i] = set()
                    self.lemmas[i] = None
 </s> add  </s> remove                     words=words, tags=tags, heads=heads, deps=deps,
                    entities=entities, morphs=morphs, lemmas=lemmas,
 </s> add                     words=words, tags=tags, pos=pos, morphs=morphs,
                    lemmas=lemmas, heads=heads, deps=deps, entities=entities, </s> remove             self.morphs = [None] * len(doc)
            self.lemmas = [None] * len(doc)
 </s> add 
                    self.pos[i] = "SPACE"
                    self.morphs[i] = None
                    self.lemmas[i] = None
                  if doc[i].text.isspace():
                      self.words[i] = doc[i].text
                      self.tags[i] = "_SP"
                    self.pos[i] = "SPACE"
                    self.morphs[i] = None
                    self.lemmas[i] = None
                      self.heads[i] = None
                      self.labels[i] = None
                      self.ner[i] = None
                      self.sent_starts[i] = 0
                  if gold_i is None:
                      if i in i2j_multi:
keep keep add keep keep 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