original_docstring: 
      Add the truth-in-a-model value to each semantic representation
      for each syntactic parse of each input sentences.
  
      :param inputs: a list of sentences
      :type inputs: list(str)
      :param grammar: ``FeatureGrammar`` or name of feature-based grammar
      :type grammar: nltk.grammar.FeatureGrammar
      :return: a mapping from sentences to lists of triples (parse-tree, semantic-representations, evaluation-in-model)
      :rtype: list(list(tuple(nltk.tree.Tree, nltk.sem.logic.ConstantExpression, bool or dict(str): bool)))
      
docstring: Add the truth-in-a-model value to each semantic representation
  for each syntactic parse of each input sentences.
docstring_tokens: Add the truth - in - a - model value to each semantic representation for each syntactic parse of each input sentences .
code: def evaluate_sents(inputs, grammar, model, assignment, trace=0):
      """
      Add the truth-in-a-model value to each semantic representation
      for each syntactic parse of each input sentences.
  
      :param inputs: a list of sentences
      :type inputs: list(str)
      :param grammar: ``FeatureGrammar`` or name of feature-based grammar
      :type grammar: nltk.grammar.FeatureGrammar
      :return: a mapping from sentences to lists of triples (parse-tree, semantic-representations, evaluation-in-model)
      :rtype: list(list(tuple(nltk.tree.Tree, nltk.sem.logic.ConstantExpression, bool or dict(str): bool)))
      """
      return [
          [
              (syn, sem, model.evaluate("%s" % sem, assignment, trace=trace))
              for (syn, sem) in interpretations
          ]
          for interpretations in interpret_sents(inputs, grammar)
      ]
code_tokens: def evaluate_sents ( inputs , grammar , model , assignment , trace = 0 ) : return [ [ ( syn , sem , model . evaluate ( "%s" % sem , assignment , trace = trace ) ) for ( syn , sem ) in interpretations ] for interpretations in interpret_sents ( inputs , grammar ) ]
short_docstring: Add the truth-in-a-model value to each semantic representation
  for each syntactic parse of each input sentences.
short_docstring_tokens: Add the truth - in - a - model value to each semantic representation for each syntactic parse of each input sentences .
comment: """
      Add the truth-in-a-model value to each semantic representation
      for each syntactic parse of each input sentences.
  
      :param inputs: a list of sentences
      :type inputs: list(str)
      :param grammar: ``FeatureGrammar`` or name of feature-based grammar
      :type grammar: nltk.grammar.FeatureGrammar
      :return: a mapping from sentences to lists of triples (parse-tree, semantic-representations, evaluation-in-model)
      :rtype: list(list(tuple(nltk.tree.Tree, nltk.sem.logic.ConstantExpression, bool or dict(str): bool)))
      """