43 lines
1.5 KiB
Python
43 lines
1.5 KiB
Python
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# Natural Language Toolkit: Translation metrics
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#
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# Copyright (C) 2001-2019 NLTK Project
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# Author: Will Zhang <wilzzha@gmail.com>
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# Guan Gui <ggui@student.unimelb.edu.au>
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# Steven Bird <stevenbird1@gmail.com>
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# URL: <http://nltk.org/>
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# For license information, see LICENSE.TXT
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from __future__ import division
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def alignment_error_rate(reference, hypothesis, possible=None):
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"""
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Return the Alignment Error Rate (AER) of an alignment
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with respect to a "gold standard" reference alignment.
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Return an error rate between 0.0 (perfect alignment) and 1.0 (no
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alignment).
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>>> from nltk.translate import Alignment
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>>> ref = Alignment([(0, 0), (1, 1), (2, 2)])
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>>> test = Alignment([(0, 0), (1, 2), (2, 1)])
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>>> alignment_error_rate(ref, test) # doctest: +ELLIPSIS
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0.6666666666666667
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:type reference: Alignment
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:param reference: A gold standard alignment (sure alignments)
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:type hypothesis: Alignment
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:param hypothesis: A hypothesis alignment (aka. candidate alignments)
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:type possible: Alignment or None
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:param possible: A gold standard reference of possible alignments
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(defaults to *reference* if None)
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:rtype: float or None
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"""
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if possible is None:
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possible = reference
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else:
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assert reference.issubset(possible) # sanity check
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return 1.0 - (len(hypothesis & reference) + len(hypothesis & possible)) / float(
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len(hypothesis) + len(reference)
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)
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