code: def alignment_error_rate(reference, hypothesis, possible=None):
      """
      Return the Alignment Error Rate (AER) of an alignment
      with respect to a "gold standard" reference alignment.
      Return an error rate between 0.0 (perfect alignment) and 1.0 (no
      alignment).
  
          >>> from nltk.translate import Alignment
          >>> ref = Alignment([(0, 0), (1, 1), (2, 2)])
          >>> test = Alignment([(0, 0), (1, 2), (2, 1)])
          >>> alignment_error_rate(ref, test) # doctest: +ELLIPSIS
          0.6666666666666667
  
      :type reference: Alignment
      :param reference: A gold standard alignment (sure alignments)
      :type hypothesis: Alignment
      :param hypothesis: A hypothesis alignment (aka. candidate alignments)
      :type possible: Alignment or None
      :param possible: A gold standard reference of possible alignments
          (defaults to *reference* if None)
      :rtype: float or None
      """
  
      if possible is None:
          possible = reference
      else:
          assert reference.issubset(possible)  # sanity check
  
      return 1.0 - (
          len(hypothesis & reference) + len(hypothesis & possible)
      ) / float(len(hypothesis) + len(reference))
  
label_desc: Use image node_id 1 for calling a global function with example usage: alignment_error_rate(reference, hypothesis, possible) and returns: unknown