          tags = []
          heads = []
          labels = []
          ner = []
          morphs = []
          lemmas = []
          sent_starts = []
          brackets = []
          for sent in paragraph["sentences"]:
              sent_start_i = len(words)
              for i, token in enumerate(sent["tokens"]):
 
</s> remove         self.morphs = morphs if morphs else []
        self.lemmas = lemmas if lemmas else []
 </s> add  </s> remove         s_ids, s_words, s_tags, s_heads = [], [], [], []
        s_deps, s_ents, s_morphs, s_lemmas, s_sent_starts = [], [], [], [], []
 </s> add         s_ids, s_words, s_tags, s_pos, s_morphs = [], [], [], [], []
        s_lemmas, s_heads, s_deps, s_ents, s_sent_starts = [], [], [], [], [] </s> remove                 s_ids, s_words, s_tags, s_heads = [], [], [], []
 </s> add                 s_ids, s_words, s_tags, s_pos, s_heads = [], [], [], [], []
          tags = []
          heads = []
          labels = []
          ner = []


          sent_starts = []
          brackets = []
          for sent in paragraph["sentences"]:
              sent_start_i = len(words)
              for i, token in enumerate(sent["tokens"]):
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