      def split_sents(self):
          """ Split the token annotations into multiple Examples based on
          sent_starts and return a list of the new Examples"""
          s_example = Example(doc=None, doc_annotation=self.doc_annotation)
          s_ids, s_words, s_tags, s_heads = [], [], [], []
          s_deps, s_ents, s_morphs, s_lemmas, s_sent_starts = [], [], [], [], []
          s_brackets = []
          sent_start_i = 0
          t = self.token_annotation
          split_examples = []
          for i in range(len(t.words)):
 
</s> remove                 s_ids, s_words, s_tags, s_heads = [], [], [], []
 </s> add                 s_ids, s_words, s_tags, s_pos, s_heads = [], [], [], [], [] </s> remove                         words=s_words, tags=s_tags, heads=s_heads, deps=s_deps,
                        entities=s_ents, morphs=s_morphs, lemmas=s_lemmas,
                        sent_starts=s_sent_starts, brackets=s_brackets)
 </s> add                         words=s_words, tags=s_tags, pos=s_pos, morphs=s_morphs,
                        lemmas=s_lemmas, heads=s_heads, deps=s_deps,
                        entities=s_ents, sent_starts=s_sent_starts,
                        brackets=s_brackets) </s> remove                 json_token["lemma"] = token.lemma_
 </s> add  </s> remove         morphs = []
        lemmas = []
 </s> add 
        s_ids, s_words, s_tags, s_pos, s_morphs = [], [], [], [], []
        s_lemmas, s_heads, s_deps, s_ents, s_sent_starts = [], [], [], [], []
      def split_sents(self):
          """ Split the token annotations into multiple Examples based on
          sent_starts and return a list of the new Examples"""
          s_example = Example(doc=None, doc_annotation=self.doc_annotation)
        s_ids, s_words, s_tags, s_pos, s_morphs = [], [], [], [], []
        s_lemmas, s_heads, s_deps, s_ents, s_sent_starts = [], [], [], [], []
        s_ids, s_words, s_tags, s_pos, s_morphs = [], [], [], [], []
        s_lemmas, s_heads, s_deps, s_ents, s_sent_starts = [], [], [], [], []
          s_brackets = []
          sent_start_i = 0
          t = self.token_annotation
          split_examples = []
          for i in range(len(t.words)):
keep keep keep keep replace replace 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