def generate(self, dataset):
for edge in dataset.edges():
head1 = edge.entity1.head_token
head2 = edge.entity2.head_token
sentence = edge.part.sentences[edge.sentence_id]
protein_word_found = False
for token in sentence:
if token.is_entity_part(edge.part) and token.word.lower().find('protein') >= 0:
protein_word_found = True
token_from = token.features['dependency_from'][0]
if token_from == head1:
feature_name = '78_dependency_from_entity_to_protein_word_[0]'
self.add_to_feature_set(edge, feature_name)
for dependency_to in token.features['dependency_to']:
token_to = dependency_to[0]
if token_to == head1:
feature_name = '79_dependency_from_protein_word_to_entity_[0]'
self.add_to_feature_set(edge, feature_name)
path = get_path(token, head1, edge.part, edge.sentence_id, self.graphs)
if path == []:
path = [token, head1]
for tok in path:
feature_name = '80_PWPE_bow_masked_'+tok.masked_text(edge.part)+'_[0]'
self.add_to_feature_set(edge, feature_name)
feature_name = '81_PWPE_pos_'+tok.features['pos']+'_[0]'
self.add_to_feature_set(edge, feature_name)
feature_name = '82_PWPE_bow_'+tok.word+'_[0]'
self.add_to_feature_set(edge, feature_name)
all_walks = build_walks(path)
for dep_list in all_walks:
dep_path = ''
for dep in dep_list:
feature_name = '83_'+'PWPE_dep_'+dep[1]+'_[0]'
self.add_to_feature_set(edge, feature_name)
dep_path += dep[1]
feature_name = '84_PWPE_dep_full+'+dep_path+'_[0]'
self.add_to_feature_set(edge, feature_name)
for j in range(len(all_walks)):
dir_grams = ''
for i in range(len(path)-1):
cur_walk = all_walks[j]
if cur_walk[i][0] == path[i]:
dir_grams += 'F'
else:
dir_grams += 'R'
feature_name = '85_PWPE_dep_gram_'+dir_grams+'_[0]'
self.add_to_feature_set(edge, feature_name)
if protein_word_found:
feature_name = '86_protein_word_found_[0]'
self.add_to_feature_set(edge, feature_name)
else:
feature_name = '87_protein_not_word_found_[0]'
self.add_to_feature_set(edge, feature_name)
def generate(self, dataset):
for edge in dataset.edges():
head1 = edge.entity1.head_token
head2 = edge.entity2.head_token
sentence = edge.part.sentences[edge.sentence_id]
path = []
path = get_path(head1, head2, edge.part, edge.sentence_id, self.graphs)
if len(path)==0:
path = [head1, head2]
self.path_length_features(path, edge)
self.token_feature_generator.token_features(path[0], 'token_term_1_', edge)
self.token_feature_generator.token_features(path[-1], 'token_term_2_', edge)
self.path_dependency_features(path, edge)
base_words = ['interact', 'bind', 'coactivator', 'complex', 'mediate']
words = []
for word in base_words:
words.append(self.stemmer.stem(word))
self.path_constituents(path, edge, words)
self.path_grams(2, path, edge)
self.path_grams(3, path, edge)
self.path_grams(4, path, edge)
self.path_edge_features(path, edge)