class_docstr: Coreference on Winogender schemas (Rudinger et al. 2018).
class_docstr_tok: ["Coreference","on","Winogender","schemas","(","Rudinger","et","al",".","2018",")","."]
code: def spec(self):
      return {
          "text": lit_types.TextSegment(),
          "tokens": lit_types.Tokens(parent="text"),
          "coref": lit_types.EdgeLabels(align="tokens"),
          # Metadata fields for filtering and analysis.
          "occupation": lit_types.CategoryLabel(),
          "participant": lit_types.CategoryLabel(),
          "answer": lit_types.CategoryLabel(vocab=ANSWER_VOCAB),
          "someone": lit_types.CategoryLabel(vocab=["True", "False"]),
          "pronouns": lit_types.CategoryLabel(
              vocab=list(PRONOUNS_BY_GENDER.values())
          ),
          "pronoun_type": lit_types.CategoryLabel(
              vocab=["NOM", "POSS", "ACC"]
          ),
          "gender": lit_types.CategoryLabel(
              vocab=[g.name for g in Gender]
          ),
          "pf_bls": lit_types.Scalar(),
      }
  
file_path: lit/lit_nlp/examples/coref/datasets/winogender.py
imports: import enum
  import os
  from typing import Optional
  from absl import logging
  from lit_nlp.api import dataset
  from lit_nlp.api import dtypes
  from lit_nlp.api import types
  from lit_nlp.lib import file_cache
  import pandas
label_desc: Use image node_id 2 for calling the WinogenderDataset obj's underlying member method code with example usage: obj.spec() and returns: dict