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)