                      if i in i2j_multi:
                          self.words[i] = words[i2j_multi[i]]
                          self.tags[i] = tags[i2j_multi[i]]
                          self.morphs[i] = morphs[i2j_multi[i]]
                          self.lemmas[i] = lemmas[i2j_multi[i]]
                          self.sent_starts[i] = sent_starts[i2j_multi[i]]
                          is_last = i2j_multi[i] != i2j_multi.get(i+1)
                          is_first = i2j_multi[i] != i2j_multi.get(i-1)
                          # Set next word in multi-token span as head, until last
 
</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             if not heads:
                heads = [None for _ in words]
            if not deps:
                deps = [None for _ in words]
 </s> add             if not pos:
                pos = [None for _ in words]
                        self.pos[i] = pos[i2j_multi[i]]
                      if i in i2j_multi:
                          self.words[i] = words[i2j_multi[i]]
                          self.tags[i] = tags[i2j_multi[i]]
                        self.pos[i] = pos[i2j_multi[i]]
                          self.morphs[i] = morphs[i2j_multi[i]]
                          self.lemmas[i] = lemmas[i2j_multi[i]]
                          self.sent_starts[i] = sent_starts[i2j_multi[i]]
                          is_last = i2j_multi[i] != i2j_multi.get(i+1)
                          is_first = i2j_multi[i] != i2j_multi.get(i-1)
                          # Set next word in multi-token span as head, until last
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