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 path_grams(self, n, path, edge):
token1 = path[0]
token2 = path[-1]
token1_anns = self.token_feature_generator.annotated_types(token1, edge)
token2_anns = self.token_feature_generator.annotated_types(token2, edge)
self.build_walk_paths(path, edge)
all_walks = build_walks(path)
for i in range(len(all_walks)):
dir_grams = ''
for j in range(len(path)-1):
current_walk = all_walks[i]
if current_walk[j][0].features['dependency_from'][0]==path[i]:
dir_grams += 'F'
else:
dir_grams += 'R'
if i>=n-1:
style_gram = ''
style_gram = dir_grams[i-n+1:i+1]
edge_gram = 'dep_gram_' + style_gram
for k in range(1, n):
token = edge.part.sentences[edge.sentence_id][(path[i-(n-1)+k]).features['id']-1]
self.token_feature_generator.token_features(token, 'tok_'+style_gram, edge)
for k in range(n):
dep = current_walk[i-(n-1)+k][1]
feature_name = '57_dep_'+style_gram+'_'+str(k)+'_'+dep+'_[0]'
self.add_to_feature_set(edge, feature_name)
edge_gram += '_' + dep
feature_name = '58_'+edge_gram+'_[0]'
self.add_to_feature_set(edge, feature_name)
for ann1 in token1_anns:
for ann2 in token2_anns:
feature_name = '59_'+ann1+'_'+edge_gram+'_'+ann2+'_[0]'
self.add_to_feature_set(edge, feature_name)
feature_name = '60_edge_directions_' + dir_grams + '_[0]'
self.add_to_feature_set(edge, feature_name)
