def main():
search = SearchIndex(dictionary_file, postings_file)
with open(query_file, 'r') as fquery:
with open(output_file, 'w') as foutput:
for query in fquery.readlines():
result = search.search(query)
# print result
foutput.write(result + '\n')
def __init__(self, aerospike_connector):
self._search_index = SearchIndex(aerospike_connector)
if len(tuples) > MAX_CANDIDATE_TUPLES:
tuples = set(random.sample(tuples, MAX_CANDIDATE_TUPLES))
sources = extract_dimension_from_tuples_as_list(tuples, 0)
relations = extract_dimension_from_tuples_as_list(tuples, 1)
targets = extract_dimension_from_tuples_as_list(tuples, 2)
output_row = {
'question': question,
'qn_entities': get_str_of_seq(qn_entities),
'ans_entities': get_str_of_seq(ans_entities),
'sources': get_str_of_seq(sources),
'relations': get_str_of_seq(relations),
'targets': get_str_of_seq(targets)
}
writer.writerow(output_row)
if __name__ == "__main__":
parser = argparse.ArgumentParser(description='Specify arguments')
parser.add_argument('--input_examples', help='the raw qa pairs', required=True)
parser.add_argument('--input_graph', help='the graph file', required=True)
parser.add_argument('--input_doc', help='the doc file', required=False)
parser.add_argument('--stopwords', help='stopwords file', required=False)
parser.add_argument('--output_examples', help='the processed output file', required=True)
args = parser.parse_args()
#global variables
knowledge_base = KnowledgeGraph(args.input_graph, unidirectional=False)
search_index = SearchIndex(args.input_doc, args.stopwords)
stop_vocab = read_file_as_dict(args.stopwords)
question_parser = QuestionParser(knowledge_base.get_entities(), stop_vocab)
main(args)
