def convert_question(dag, candidates, question, labels, pos_tagged, filename, path):
"""Convert a question from dataset to list of phrases
Keyword arguments:
dag -- model for dag parsing
candidates -- list of lists of entity candidates
question -- question in object form
labels -- list of lists phrase tags
pos_tagged -- list of lists of POS tags
filename -- output file name
path -- path to files
"""
phr, pos = sr.parse_to_phrases([question], [labels], [pos_tagged])
DAG = sr.shift_reduce(phr[0], pos[0], dag, 50).dag
ent_path = path + "ent_lr_trn_641.pickle"
edge_path = path + "edge_lr_trn.pickle"
rel_path = path + "relation_lr_trn_641.pickle"
bow_path = path + "bow_dict_all.pickle"
g_path = path + "rel_dict.pickle"
dct_path = path + "edge_dict.pickle"
a_path = path + "bow_all_words_dict.pickle"
intent = el.label_all(phr[0], DAG, candidates, ent_path, edge_path, rel_path, bow_path, g_path, dct_path, a_path)
queries = sq.convert_to_queries(intent)
if len(queries) > 0:
# sq.create_query_file(filename, queries, phr[0])
query = sq.create_query(queries, phr[0])
else:
query = "SELECT ?a WHERE {}"
return sq.query_fb_endpoint(query, 'http://freebase.ailao.eu:3030/freebase/query')
def get_phrases_free(question, model, nlp_path, java_path):
"""Convert a string question to list of phrases
Keyword arguments:
question -- question in string form
model -- model for phrase detection
nlp_path -- path to Stanford NLP tagger
java_path -- path to Java instalation
"""
pd_model = pickle.load(open(model))
q = Question(question, "")
utterance = question.split()
labels = []
pos = pos_tag([q])
ner = ner_tag([q], nlp_path, java_path)
l = 4
u = ["", ""] + utterance + ["", ""]
p = ['', ''] + [pp[1] for pp in pos[0]] + ['', '']
n = ['', ''] + [nn[1] for nn in ner[0]] + ['', '']
for j in range(2, len(u) - 2):
feature = construct_feature(p, u, n, j, l)
label = predict(pd_model, feature, 4)
labels.append(label)
l = label
phr, pos_t = sr.parse_to_phrases([q], [labels], pos)
candidates = el.obtain_entity_candidates(phr, 5)
return labels, pos, q, candidates
def get_phrases_free(question, model, nlp_path, java_path):
"""Convert a string question to list of phrases
Keyword arguments:
question -- question in string form
model -- model for phrase detection
nlp_path -- path to Stanford NLP tagger
java_path -- path to Java instalation
"""
pd_model = pickle.load(open(model))
q = Question(question, "")
utterance = question.split()
labels = []
pos = pos_tag([q])
ner = ner_tag([q], nlp_path, java_path)
l = 4
u = ["", ""] + utterance + ["", ""]
p = ['', ''] + [pp[1] for pp in pos[0]] + ['', '']
n = ['', ''] + [nn[1] for nn in ner[0]] + ['', '']
for j in range(2, len(u)-2):
feature = construct_feature(p, u, n, j, l)
label = predict(pd_model, feature, 4)
labels.append(label)
l = label
phr, pos_t = sr.parse_to_phrases([q], [labels], pos)
candidates = el.obtain_entity_candidates(phr, 5)
return labels, pos, q, candidates
def convert_question(dag, candidates, question, labels, pos_tagged, filename,
path):
"""Convert a question from dataset to list of phrases
Keyword arguments:
dag -- model for dag parsing
candidates -- list of lists of entity candidates
question -- question in object form
labels -- list of lists phrase tags
pos_tagged -- list of lists of POS tags
filename -- output file name
path -- path to files
"""
phr, pos = sr.parse_to_phrases([question], [labels], [pos_tagged])
DAG = sr.shift_reduce(phr[0], pos[0], dag, 50).dag
ent_path = path + "ent_lr_trn_641.pickle"
edge_path = path + "edge_lr_trn.pickle"
rel_path = path + "relation_lr_trn_641.pickle"
bow_path = path + "bow_dict_all.pickle"
g_path = path + "rel_dict.pickle"
dct_path = path + "edge_dict.pickle"
a_path = path + "bow_all_words_dict.pickle"
intent = el.label_all(phr[0], DAG, candidates, ent_path, edge_path,
rel_path, bow_path, g_path, dct_path, a_path)
queries = sq.convert_to_queries(intent)
if len(queries) > 0:
# sq.create_query_file(filename, queries, phr[0])
query = sq.create_query(queries, phr[0])
else:
query = "SELECT ?a WHERE {}"
return sq.query_fb_endpoint(
query, 'http://freebase.ailao.eu:3030/freebase/query')