class_docstr: TyDiQA dataset.
code: def spec(self) -> lit_types.Spec:
      return {
          "title": lit_types.TextSegment(),
          "context": lit_types.TextSegment(),
          "question": lit_types.TextSegment(),
          "answers_text": lit_types.MultiSegmentAnnotations(),
          "language": lit_types.CategoryLabel(
              required=False, vocab=TYDI_LANG_VOCAB
          ),
      }
  
file_path: lit/lit_nlp/examples/datasets/question_answering.py
imports: import re
  from lit_nlp.api import dataset
  from lit_nlp.api import dtypes
  from lit_nlp.api import types
  import tensorflow_datasets
label_desc: Use image node_id 2 for calling the TyDiQA obj's underlying member method code with example usage: obj.spec() and returns: dict