def test_get_ordered_words(self):
sentence = [(0, None, [(u'root', [5])]), (1, u'For', []),
(2, u'ten', []),
(3, u'points', [(u'case', [1]), (u'nummod', [2])]),
(5, u'identify', [(u'advcl', [17]), (u'nmod', [3]),
(u'dobj', [8])]), (6, u'this', []),
(7, u'English', []),
(8, u'king', [(u'det', [6]), (u'nmod', [10]),
(u'amod', [7])]), (9, u'of', []),
(10, u'Wessex', [(u'case', [9]), (u'appos', [15])]),
(12, u'the', []), (13, u'only', []), (14, u'English', []),
(15, u'king', [(u'advmod', [13]), (u'det', [12]),
(u'amod', [14])]), (16, u'to', []),
(17, u'earn', [(u'xcomp', [22]), (u'mark', [16])]),
(18, u'the', []), (19, u'epithet', [(u'det', [18])]),
(21, u'the', []),
(22, u'Great', [(u'dep', [19]), (u'det', [21])])]
vocabulary = {
'earn': 0,
'English': 1,
'epithet': 2,
'For': 3,
'Great': 4,
'identify': 5,
'king': 6,
'of': 7,
'only': 8,
'points': 9,
'ten': 10,
'the': 11,
'this': 12,
'to': 13,
'Wessex': 14
}
dep_dict = {
'advcl': 0,
'advmod': 1,
'amod': 2,
'appos': 3,
'case': 4,
'case': 5,
'dep': 6,
'det': 7,
'dobj': 8,
'mark': 9,
'nmod': 10,
'nummod': 11,
'xcomp': 12
}
answer = 'yo buddy!'
tree = tree_from_stanford_parse_tuples(sentence, answer, vocabulary,
dep_dict)
result = ' '.join(tree.get_ordered_words(vocabulary))
expected = ('For ten points identify this English king of Wessex '
'the only English king to earn the epithet the Great')
self.assertEquals(result, expected)
def create_tree(sentences_path, sentence_ID_path,
question_info_path, vocabulary_path,
dependency_path, stanford_parsed_path, tree_list_path):
"""Opens up all the data and passes it
to dependency_tree to create all trees
"""
tree_list = []
with open(sentences_path, 'rb') as f:
sentences = cPickle.load(f)
with open(sentence_ID_path, 'rb') as f:
sentences_ID = cPickle.load(f)
with open(question_info_path, 'rb') as f:
question_info = cPickle.load(f)
with open(vocabulary_path, 'rb') as f:
vocabulary = cPickle.load(f)
with open(dependency_path, 'rb') as f:
dependency = cPickle.load(f)
with open(stanford_parsed_path, 'rb') as f:
stanford_parsed = cPickle.load(f)
for k in range(len(sentences)):
answer = question_info[sentences_ID[k]][2]
tree = tree_from_stanford_parse_tuples(stanford_parsed[k], answer,
vocabulary, dependency)
tree_list.append(tree)
with open(tree_list_path, 'wb') as f:
cPickle.dump(tree_list, f)
