def __init__(self,
endpoint='http://localhost:5001/qg/api/v1.0/query',
cache_path="",
use_cache=True):
self.endpoint = endpoint
self.cache_path = cache_path
self.use_cache = use_cache
self.cache = {}
if self.use_cache:
Utils.makedirs(cache_path)
self.cache_path = os.path.join(cache_path, "sqg.cache")
self.__load_cache()
def __init__(self,
endpoint='http://localhost:5000/processQuery',
cache_path="",
use_cache=True):
self.endpoint = endpoint
self.cache_path = cache_path
self.use_cache = use_cache
self.cache = {}
if self.use_cache:
Utils.makedirs(cache_path)
self.cache_path = os.path.join(cache_path, "earl.cache")
self.__load_cache()
from common.utility.utils import Utils
from common.component.chunker.SENNAChunker import SENNAChunker
from common.component.chunker.classifierChunkParser import ClassifierChunkParser
from common.component.chunker.goldChunker import GoldChunker
import pickle as pk
import nltk
import os
if __name__ == "__main__":
test_sentence = "Was winston churchill the prime minister of Selwyn Lloyd?"
test_sentence = "What is the hometown of Nader Guirat, where Josef Johansson was born too?"
base_dir = "../../"
model_dir = os.path.join(base_dir, "models")
Utils.makedirs(model_dir)
with open('../../data/LC-QUAD/linked_IOB.pk') as data_file:
orginal_dataset = pk.load(data_file)
dataset = [item[1:] for item in orginal_dataset]
idx = int(len(dataset) * 0.9)
# idx = -1
train_sents = dataset[:idx]
test_sents = dataset[idx + 1:]
test_sents_tree = [nltk.chunk.conlltags2tree(item) for item in test_sents]
gold_chunker = GoldChunker({item[0]: item[1:] for item in orginal_dataset})
print "\nGold Chunker"
print gold_chunker.evaluate(test_sents_tree)
SENNA_chunker = SENNAChunker()
print "SENNA Chunker"
print SENNA_chunker.evaluate(test_sents_tree)