          return cls(doc, words=token_annotation.words,
                     tags=token_annotation.tags,
                     heads=token_annotation.heads,
                     deps=token_annotation.deps,
                     entities=token_annotation.entities,
                     sent_starts=token_annotation.sent_starts,
                     cats=doc_annotation.cats,
 
</s> remove                    morphs=token_annotation.morphs,
                   lemmas=token_annotation.lemmas,
 </s> add  </s> remove     def get_morph(self, i):
        return self.morphs[i] if i < len(self.morphs) else set()

    def get_lemma(self, i):
        return self.lemmas[i] if i < len(self.lemmas) else ""

 </s> add  </s> remove                    morphs=token_dict.get("morphs", None),
                   lemmas=token_dict.get("lemmas", None),
 </s> add 
                   pos=token_annotation.pos,
                   morphs=token_annotation.morphs,
                   lemmas=token_annotation.lemmas,
          return cls(doc, words=token_annotation.words,
                     tags=token_annotation.tags,
                   pos=token_annotation.pos,
                   morphs=token_annotation.morphs,
                   lemmas=token_annotation.lemmas,
                     heads=token_annotation.heads,
                     deps=token_annotation.deps,
                     entities=token_annotation.entities,
                     sent_starts=token_annotation.sent_starts,
                     cats=doc_annotation.cats,
keep add 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