if __name__ == "__main__":
db = pickle.load(open("dump/database-simplified.dump"))
fin = codecs.open(INPUT_FILE, "r", "utf-8")
lines = map(lambda l: l.strip(), fin.readlines())
fin.close()
ids = []
queries = []
for line in lines:
parts = line.strip().split()
ids.append(parts[0])
if INPUT_FILE.startswith("test"):
queries.append(parts[1])
else:
queries.append(parts[0])
if USE_KNN:
search = Search(database=db)
search.embedding = Word2Vec.load("dump/w2v-model-simplified.dump")
else:
search = Search(database=db)
fout = codecs.open(INPUT_FILE + "-output.txt", "w", "utf-8")
for id, query in zip(ids, queries):
results = search.answer(query, length=2, open=OPEN_MODE)
if results:
score, _, answer, sentence = results[0]
# result = (score, sentence, answer)
fout.write("%s\t%s\n" % (id, answer))
else:
fout.write("%s\t%s\n" % (id, "none"))
#coding=utf-8
import codecs
from data import Database
from search import Search
from question import parseQuestion
if __name__ == "__main__":
#db = Database("data/zhwiki-extracted/", conditions = [
# Database.cond_length(50),
# Database.cond_title(lambda t: not t.startswith("Wikipedia:")),
# Database.cond_title(lambda t: not t.startswith("File:")),
# Database.cond_title(lambda t: not t.startswith("Draft:"))
#])
import pickle
db = pickle.load(open("dump/database-simplified.dump"))
fin = codecs.open("sample.txt", "r", "utf-8")
lines = map(lambda l: l.strip(), fin.readlines())
fin.close()
queries = map(lambda l: l.split()[0], lines)
fout = codecs.open("output-50.txt", "w", "utf-8")
search = Search(db)
for query in queries:
fout.write("%s\n" % query)
results = search.answer(query, length=2, open=True)
for score, _, answer, sentence in results:
# result = (score, sentence, answer)
fout.write("%d\t%s\t%s\n" % (score, answer, sentence))
fout.write("---------------------------------\n")