class_docstr: Recognizing Textual Entailment.
  
  See https://www.tensorflow.org/datasets/catalog/glue#gluerte.
class_docstr_tok: ["Recognizing","Textual","Entailment",".","See","https",":","\/\/www.tensorflow.org\/datasets\/catalog\/glue","#","gluerte","."]
code: def spec(self):
      return {
          "sentence1": lit_types.TextSegment(),
          "sentence2": lit_types.TextSegment(),
          "label": lit_types.CategoryLabel(vocab=self.LABELS),
      }
  
imports: from typing import Optional
  from lit_nlp.api import dataset
  from lit_nlp.api import types
  from lit_nlp.lib import file_cache
  from lit_nlp.lib import utils
  import pandas
  import tensorflow_datasets
label_desc: Use image node_id 2 for calling the RTEData obj's underlying member method code with example usage: obj.spec() and returns: dict