Source code for nltk.test.unit.test_rte_classify

# -*- coding: utf-8 -*-
from __future__ import print_function, unicode_literals

import unittest

from nltk.corpus import rte as rte_corpus
from nltk.classify.rte_classify import RTEFeatureExtractor, rte_features, rte_classifier

expected_from_rte_feature_extration = """
alwayson        => True
ne_hyp_extra    => 0
ne_overlap      => 1
neg_hyp         => 0
neg_txt         => 0
word_hyp_extra  => 3
word_overlap    => 3

alwayson        => True
ne_hyp_extra    => 0
ne_overlap      => 1
neg_hyp         => 0
neg_txt         => 0
word_hyp_extra  => 2
word_overlap    => 1

alwayson        => True
ne_hyp_extra    => 1
ne_overlap      => 1
neg_hyp         => 0
neg_txt         => 0
word_hyp_extra  => 1
word_overlap    => 2

alwayson        => True
ne_hyp_extra    => 1
ne_overlap      => 0
neg_hyp         => 0
neg_txt         => 0
word_hyp_extra  => 6
word_overlap    => 2

alwayson        => True
ne_hyp_extra    => 1
ne_overlap      => 0
neg_hyp         => 0
neg_txt         => 0
word_hyp_extra  => 4
word_overlap    => 0

alwayson        => True
ne_hyp_extra    => 1
ne_overlap      => 0
neg_hyp         => 0
neg_txt         => 0
word_hyp_extra  => 3
word_overlap    => 1
"""


[docs]class RTEClassifierTest(unittest.TestCase): # Test the feature extraction method.
[docs] def test_rte_feature_extraction(self): pairs = rte_corpus.pairs(['rte1_dev.xml'])[:6] test_output = [ "%-15s => %s" % (key, rte_features(pair)[key]) for pair in pairs for key in sorted(rte_features(pair)) ] expected_output = expected_from_rte_feature_extration.strip().split('\n') # Remove null strings. expected_output = list(filter(None, expected_output)) self.assertEqual(test_output, expected_output)
# Test the RTEFeatureExtractor object.
[docs] def test_feature_extractor_object(self): rtepair = rte_corpus.pairs(['rte3_dev.xml'])[33] extractor = RTEFeatureExtractor(rtepair) self.assertEqual(extractor.hyp_words, {'member', 'China', 'SCO.'}) self.assertEqual(extractor.overlap('word'), set()) self.assertEqual(extractor.overlap('ne'), {'China'}) self.assertEqual(extractor.hyp_extra('word'), {'member'})
# Test the RTE classifier training.
[docs] def test_rte_classification_without_megam(self): clf = rte_classifier('IIS') clf = rte_classifier('GIS')
[docs] @unittest.skip("Skipping tests with dependencies on MEGAM") def test_rte_classification_with_megam(self): nltk.config_megam('/usr/local/bin/megam') clf = rte_classifier('megam') clf = rte_classifier('BFGS')