def word_depparser(sentence, is_segmented=False):
if not depparser_agent:
return []
## post request
m_input = nlpc.parse_prep_input()
m_input.sentence = str(utf8_gbk(sentence))
m_input.grain_size = 1
m_input.sentence_segmented = is_segmented
input_data = sofa.serialize(m_input)
for i in range(5):
try:
ret, output_data = depparser_agent.call_method(input_data)
break
except Exception as e:
continue
if len(output_data) == 0:
sys.stderr.write('No result' + sentence + '\n')
return []
## get results
m_output = nlpc.depparser_output()
m_output = sofa.deserialize(output_data, type(m_output))
tokens = m_output.items
depparser_list = []
for i in range(len(tokens)):
if len(tokens[i].deprel.strip()) == 0:
tokens[i].deprel = '_'
word = gbk_utf8(tokens[i].word)
depparser_list.append((word, tokens[i].deprel))
return depparser_list
def word_depparser(sentence, is_segmented=False):
if not depparser_agent:
return [];
## post request
m_input = nlpc.parse_prep_input()
m_input.sentence = str(utf8_gbk(sentence))
m_input.grain_size = 1
m_input.sentence_segmented = is_segmented
input_data = sofa.serialize(m_input)
for i in range(5) :
try:
ret, output_data = depparser_agent.call_method(input_data)
break
except Exception as e:
continue
if len(output_data) == 0:
sys.stderr.write('No result' + sentence + '\n')
return []
## get results
m_output = nlpc.depparser_output()
m_output = sofa.deserialize(output_data, type(m_output))
tokens = m_output.items
depparser_list = []
for i in range(len(tokens)):
if len(tokens[i].deprel.strip()) == 0:
tokens[i].deprel = '_'
word = gbk_utf8(tokens[i].word)
depparser_list.append((word, tokens[i].deprel))
return depparser_list
def word_ner(sentence):
if not wordner_agent:
return [];
language_id = 0
output_id = 1
m_input = nlpc.wordner_input()
m_input.lang_id = int(1)
m_input.query = str(utf8_gbk(sentence))
input_data = sofa.serialize(m_input)
for i in range(5):
try:
ret, output_data = wordner_agent.call_method(input_data)
break
except Exception as e:
continue
if len(output_data) == 0:
sys.stderr.write('The server returns None.' + '\n')
return [];
m_output = nlpc.wordner_output()
m_output = sofa.deserialize(output_data, type(m_output))
tags = m_output.tags
tags_size = len(tags)
word_ner_list = [];
for i in range(tags_size):
word_ner_list.append((gbk_utf8(tags[i].term), str(tags[i].type), trans_id_short[tags[i].type]));
'''
sys.stderr.write(gbk_utf8(tags[i].term) + ' ')
if trans_id_short.has_key(tags[i].type):
sys.stderr.write(trans_id_short[tags[i].type] + '\t')
else:
sys.stderr.write('NOR' + '\t')
sys.stderr.write('\n')
'''
return word_ner_list;
def word_rank(sentence):
if not wordrank_agent:
return [];
## post request
m_input = nlpc.wordseg_input()
m_input.lang_id = int(0)
m_input.lang_para = int(0)
m_input.query = str(utf8_gbk(sentence))
input_data = sofa.serialize(m_input)
for i in range(5) :
try:
ret, output_data = wordrank_agent.call_method(input_data)
break
except Exception as e:
pass;
if len(output_data) == 0:
sys.stderr.write('No result' + sentence + '\n')
return []
## get results
# wordrank_result
m_output = nlpc.wordrank_output()
m_output = sofa.deserialize(output_data, type(m_output))
rank_result_list = list()
list_size = len(m_output.nlpc_trunks_pn)
for i in range(list_size):
word = m_output.nlpc_trunks_pn[i].buffer
word = gbk_utf8(word)
rank = m_output.nlpc_trunks_pn[i].rank
wght = round(m_output.nlpc_trunks_pn[i].weight,3)
rank_result_list.append((word, rank, wght))
return rank_result_list
def word_seg(sent):
m_input = nlpc.wordseg_input()
m_input.query = str(utf8_gbk(sent))
m_input.lang_id = int(0)
m_input.lang_para = int(0)
input_data = sofa.serialize(m_input)
for i in range(5) :
try:
ret, output_data = wordseg_agent.call_method(input_data)
break
except Exception as e:
continue
if len(output_data) == 0:
return [];
m_output = nlpc.wordseg_output()
m_output = sofa.deserialize(output_data, type(m_output))
m_output = m_output.scw_out
ret_data = []
##seg
for i in range(m_output.wpbtermcount):
posidx = GET_TERM_POS(m_output.wpbtermpos[i])
poslen = GET_TERM_LEN(m_output.wpbtermpos[i])
word = m_output.wpcompbuf[posidx : posidx + poslen]
ret_data.append((str(posidx), str(poslen), gbk_utf8(word)))
'''
for i in range(m_output.wsbtermcount):
posidx = GET_TERM_POS(m_output.wsbtermpos[i])
poslen = GET_TERM_LEN(m_output.wsbtermpos[i])
word = m_output.wordsepbuf[posidx : posidx + poslen]
ret_data.append((posidx, poslen, word))
'''
return ret_data
def word_pos(sentence):
if not wordpos_agent:
return [];
## post request
m_input = nlpc.wordseg_input()
m_input.lang_id = int(0)
m_input.lang_para = int(0)
m_input.query = str(utf8_gbk(sentence))
input_data = sofa.serialize(m_input)
for i in range(5) :
try:
ret, output_data = wordpos_agent.call_method(input_data)
break
except Exception as e:
pass;
if len(output_data) == 0:
sys.stderr.write('No result' + sentence + '\n')
return []
## get results
# wordpos result
m_output = nlpc.wordpos_output()
m_output = sofa.deserialize(output_data, type(m_output))
tokens_size = len(m_output.nlpc_tokens)
segment_result = []
for i in range(tokens_size):
stag = get_pos_str(m_output.nlpc_tokens[i].type)
if stag:
word = m_output.nlpc_tokens[i].buffer
word = gbk_utf8(word)
segment_result.append((word, stag))
return segment_result
def word_ner(sentence):
if not wordner_agent:
return []
language_id = 0
output_id = 1
m_input = nlpc.wordner_input()
m_input.lang_id = int(1)
m_input.query = str(utf8_gbk(sentence))
input_data = sofa.serialize(m_input)
for i in range(5):
try:
ret, output_data = wordner_agent.call_method(input_data)
break
except Exception as e:
continue
if len(output_data) == 0:
sys.stderr.write('The server returns None.' + '\n')
return []
m_output = nlpc.wordner_output()
m_output = sofa.deserialize(output_data, type(m_output))
tags = m_output.tags
tags_size = len(tags)
word_ner_list = []
for i in range(tags_size):
word_ner_list.append((gbk_utf8(tags[i].term), str(tags[i].type),
trans_id_short[tags[i].type]))
'''
sys.stderr.write(gbk_utf8(tags[i].term) + ' ')
if trans_id_short.has_key(tags[i].type):
sys.stderr.write(trans_id_short[tags[i].type] + '\t')
else:
sys.stderr.write('NOR' + '\t')
sys.stderr.write('\n')
'''
return word_ner_list
def word_rank(sentence):
if not wordrank_agent:
return []
## post request
m_input = nlpc.wordseg_input()
m_input.lang_id = int(0)
m_input.lang_para = int(0)
m_input.query = str(utf8_gbk(sentence))
input_data = sofa.serialize(m_input)
for i in range(5):
try:
ret, output_data = wordrank_agent.call_method(input_data)
break
except Exception as e:
pass
if len(output_data) == 0:
sys.stderr.write('No result' + sentence + '\n')
return []
## get results
# wordrank_result
m_output = nlpc.wordrank_output()
m_output = sofa.deserialize(output_data, type(m_output))
rank_result_list = list()
list_size = len(m_output.nlpc_trunks_pn)
for i in range(list_size):
word = m_output.nlpc_trunks_pn[i].buffer
word = gbk_utf8(word)
rank = m_output.nlpc_trunks_pn[i].rank
wght = round(m_output.nlpc_trunks_pn[i].weight, 3)
rank_result_list.append((word, rank, wght))
return rank_result_list
def word_pos(sentence):
if not wordpos_agent:
return []
## post request
m_input = nlpc.wordseg_input()
m_input.lang_id = int(0)
m_input.lang_para = int(0)
m_input.query = str(utf8_gbk(sentence))
input_data = sofa.serialize(m_input)
for i in range(5):
try:
ret, output_data = wordpos_agent.call_method(input_data)
break
except Exception as e:
pass
if len(output_data) == 0:
sys.stderr.write('No result' + sentence + '\n')
return []
## get results
# wordpos result
m_output = nlpc.wordpos_output()
m_output = sofa.deserialize(output_data, type(m_output))
tokens_size = len(m_output.nlpc_tokens)
segment_result = []
for i in range(tokens_size):
stag = get_pos_str(m_output.nlpc_tokens[i].type)
if stag:
word = m_output.nlpc_tokens[i].buffer
word = gbk_utf8(word)
segment_result.append((word, stag))
return segment_result
def word_seg(sent):
m_input = nlpc.wordseg_input()
m_input.query = str(utf8_gbk(sent))
m_input.lang_id = int(0)
m_input.lang_para = int(0)
input_data = sofa.serialize(m_input)
for i in range(5):
try:
ret, output_data = wordseg_agent.call_method(input_data)
break
except Exception as e:
continue
if len(output_data) == 0:
return []
m_output = nlpc.wordseg_output()
m_output = sofa.deserialize(output_data, type(m_output))
m_output = m_output.scw_out
ret_data = []
##seg
for i in range(m_output.wpbtermcount):
posidx = GET_TERM_POS(m_output.wpbtermpos[i])
poslen = GET_TERM_LEN(m_output.wpbtermpos[i])
word = m_output.wpcompbuf[posidx:posidx + poslen]
ret_data.append((str(posidx), str(poslen), gbk_utf8(word)))
'''
for i in range(m_output.wsbtermcount):
posidx = GET_TERM_POS(m_output.wsbtermpos[i])
poslen = GET_TERM_LEN(m_output.wsbtermpos[i])
word = m_output.wordsepbuf[posidx : posidx + poslen]
ret_data.append((posidx, poslen, word))
'''
return ret_data
def word_lmscore(sentence):
if not lmscore_agent:
return 0.0;
m_input = nlpc.lmscore_input()
m_input.query = str(utf8_gbk(sentence));
m_input.debug_flag = True
input_data = sofa.serialize(m_input)
for i in range(5):
try:
ret, output_data = lmscore_agent.call_method(input_data)
break
except Exception as e:
continue
if len(output_data) == 0:
return 0.0
m_output = nlpc.lmscore_output()
m_output = sofa.deserialize(output_data, type(m_output))
return m_output.result.prob;
def _sim(self,q1,q2): m_input = textsim.textsim_input() m_input.query1 = q1 m_input.query2 = q2 input_data = sofa.serialize(m_input) for i in range(5) : try: ret, output_data = self.textsim_agent.call_method(input_data) break except Exception as e: #print e output_data='' continue if len(output_data) == 0: pass else: m_output = textsim.textsim_output() m_output = sofa.deserialize(output_data, type(m_output)) return m_output.textsim
def _sim(self, q1, q2):
m_input = textsim.textsim_input()
m_input.query1 = q1
m_input.query2 = q2
input_data = sofa.serialize(m_input)
for i in range(5):
try:
ret, output_data = self.textsim_agent.call_method(input_data)
break
except Exception as e:
#print e
output_data = ''
continue
if len(output_data) == 0:
pass
else:
m_output = textsim.textsim_output()
m_output = sofa.deserialize(output_data, type(m_output))
return m_output.textsim
def word_lmscore(sentence):
if not lmscore_agent:
return 0.0
m_input = nlpc.lmscore_input()
m_input.query = str(utf8_gbk(sentence))
m_input.debug_flag = True
input_data = sofa.serialize(m_input)
for i in range(5):
try:
ret, output_data = lmscore_agent.call_method(input_data)
break
except Exception as e:
continue
if len(output_data) == 0:
return 0.0
m_output = nlpc.lmscore_output()
m_output = sofa.deserialize(output_data, type(m_output))
return m_output.result.prob
def main():
sofa.use('drpc.ver_1_0_0', 'S')
sofa.use('nlpc.ver_1_0_0', 'nlpc')
conf = sofa.Config()
conf.load('./config/drpc_client.xml')
#query_agent = S.ClientAgent(conf['sofa.service.nlpc_depparser_uni_query_107'])
query_agent = S.ClientAgent(
conf['sofa.service.nlpc_depparser_uni_web_107'])
in_sentences = []
while True:
line = sys.stdin.readline()
if len(line) <= 0:
break
line = line.strip(' \t\n\r')
in_sentences.append(str(line))
if len(in_sentences) < 1000:
continue
m_input = nlpc.depparser_uni_input()
m_input.grain_size = 1
m_input.sentence_segmented = False
m_input.sentences = in_sentences
input_data = sofa.serialize(m_input)
for i in range(5):
try:
ret, output_data = query_agent.call_method(input_data)
break
except Exception as e:
continue
if len(output_data) == 0:
stdout.write('No result' + '\n')
continue
m_output = nlpc.depparser_uni_output()
m_output = sofa.deserialize(output_data, type(m_output))
dep_sentences = m_output.dep_sentences
sent_num = len(dep_sentences)
for i in range(sent_num):
dep_terms = dep_sentences[i].dep_terms
term_num = len(dep_terms)
for j in range(term_num):
if dep_terms[j].lemma.strip() is None:
dep_terms[j].lemma = '_'
if dep_terms[j].cpostag.strip() is None:
dep_terms[j].cpostag = '_'
if dep_terms[j].postag.strip() is None:
dep_terms[j].postag = '_'
if dep_terms[j].ner.strip() is None:
dep_terms[j].ner = '_'
if dep_terms[j].feat.strip() is None:
dep_terms[j].feat = '_'
if dep_terms[j].deprel.strip() is None:
dep_terms[j].deprel = '_'
sys.stdout.write(
str(j) + '\t' + dep_terms[j].word + '\t' +
dep_terms[j].lemma + '\t' + dep_terms[j].cpostag + '\t' +
dep_terms[j].postag + '\t' + dep_terms[j].ner + '\t' +
dep_terms[j].feat + '\t' + str(dep_terms[j].head) + '\t' +
dep_terms[j].deprel + '\n')
sys.stdout.write('\n')
in_sentences = []
if len(in_sentences) > 0:
m_input = nlpc.depparser_uni_input()
m_input.grain_size = 1
m_input.sentence_segmented = False
m_input.sentences = in_sentences
input_data = sofa.serialize(m_input)
m_input.sentences = in_sentences
input_data = sofa.serialize(m_input)
for i in range(5):
try:
ret, output_data = query_agent.call_method(input_data)
break
except Exception as e:
continue
if len(output_data) == 0:
stdout.write('No result' + '\n')
exit
m_output = nlpc.depparser_uni_output()
m_output = sofa.deserialize(output_data, type(m_output))
dep_sentences = m_output.dep_sentences
sent_num = len(dep_sentences)
for i in range(sent_num):
dep_terms = dep_sentences[i].dep_terms
term_num = len(dep_terms)
for j in range(term_num):
if dep_terms[j].lemma.strip() is None:
dep_terms[j].lemma = '_'
if dep_terms[j].cpostag.strip() is None:
dep_terms[j].cpostag = '_'
if dep_terms[j].postag.strip() is None:
dep_terms[j].postag = '_'
if dep_terms[j].ner.strip() is None:
dep_terms[j].ner = '_'
if dep_terms[j].feat.strip() is None:
dep_terms[j].feat = '_'
if dep_terms[j].deprel.strip() is None:
dep_terms[j].deprel = '_'
sys.stdout.write(
str(j) + '\t' + dep_terms[j].word + '\t' +
dep_terms[j].lemma + '\t' + dep_terms[j].cpostag + '\t' +
dep_terms[j].postag + '\t' + dep_terms[j].ner + '\t' +
dep_terms[j].feat + '\t' + str(dep_terms[j].head) + '\t' +
dep_terms[j].deprel + '\n')
sys.stdout.write('\n')
in_sentences = []
def main():
sofa.use('drpc.ver_1_0_0', 'S')
sofa.use('nlpc.ver_1_0_0', 'wordseg')
conf = sofa.Config()
conf.load('./config/drpc_client.xml')
wordseg_agent = S.ClientAgent(conf['sofa.service.nlpc_wordseg_3016'])
while True:
line = stdin.readline()
if len(line) <= 0:
return
line = line.decode('utf-8').encode('gbk')
m_input = wordseg.wordseg_input()
m_input.query = str(line)
m_input.lang_id = int(0)
m_input.lang_para = int(0)
input_data = sofa.serialize(m_input)
for i in range(5) :
try:
ret, output_data = wordseg_agent.call_method(input_data)
break
except Exception as e:
continue
if len(output_data) == 0:
stdout.write('No result' + '\n')
continue
m_output = wordseg.wordseg_output()
m_output = sofa.deserialize(output_data, type(m_output))
m_output = m_output.scw_out
if len(argv) == 2 and argv[1] == 'basic' or len(argv) == 1:
stdout.write('=========== Basic Word Sep Result =============' + '\n')
for i in range(m_output.wsbtermcount):
posidx = GET_TERM_POS(m_output.wsbtermpos[i])
poslen = GET_TERM_LEN(m_output.wsbtermpos[i])
word = m_output.wordsepbuf[posidx : posidx + poslen]
stdout.write('%s ' %word)
stdout.write('\n')
if len(argv) == 2 and argv[1] == 'segment' or len(argv) == 1:
stdout.write('============ Word Phrase Result ==============' + '\n')
for i in range(m_output.wpbtermcount):
posidx = GET_TERM_POS(m_output.wpbtermpos[i])
poslen = GET_TERM_LEN(m_output.wpbtermpos[i])
word = m_output.wpcompbuf[posidx : posidx + poslen]
stdout.write('%s ' %word)
stdout.write('\n')
if len(argv) == 2 and argv[1] == 'phrase' or len(argv) == 1:
stdout.write('============ Sub Phrase Result ==============' + '\n')
for i in range(m_output.spbtermcount):
posidx = GET_TERM_POS(m_output.spbtermpos[i])
poslen = GET_TERM_LEN(m_output.spbtermpos[i])
word = m_output.subphrbuf[posidx : posidx + poslen]
stdout.write('%s ' %word)
stdout.write('\n')
if len(argv) == 2 and argv[1] == 'new' or len(argv) == 1:
stdout.write('============ New Word Result ==============' + '\n')
pnewword = m_output.pnewword
for i in range(pnewword.newwordbtermcount):
posidx = GET_TERM_POS(pnewword.newwordbtermpos[i])
poslen = GET_TERM_LEN(pnewword.newwordbtermpos[i])
word = pnewword.newwordbuf[posidx : posidx + poslen]
stdout.write('%s ' %word)
stdout.write('\n')
if len(argv) == 2 and argv[1] == 'human' or len(argv) == 1:
stdout.write('=========== Human Name Result ==============' + '\n')
for i in range(m_output.namebtermcount):
posidx = GET_TERM_POS(m_output.namebtermpos[i])
poslen = GET_TERM_LEN(m_output.namebtermpos[i])
word = m_output.namebuf[posidx : posidx + poslen]
stdout.write('%s ' %word)
stdout.write('\n')
if len(argv) == 2 and argv[1] == 'book' or len(argv) == 1:
stdout.write('=============== book names =================' + '\n')
for i in range(m_output.bnbtermcount):
posidx = GET_TERM_POS(m_output.bnbtermpos[i])
poslen = GET_TERM_LEN(m_output.bnbtermpos[i])
word = m_output.booknamebuf[posidx : posidx + poslen]
stdout.write('%s ' %word)
stdout.write('\n')
def main():
sofa.use('drpc.ver_1_0_0', 'S')
sofa.use('nlpc.ver_1_0_0', 'nlpc')
conf = sofa.Config()
conf.load('./config/drpc_client.xml')
#query_agent = S.ClientAgent(conf['sofa.service.nlpc_depparser_uni_query_107'])
query_agent = S.ClientAgent(conf['sofa.service.nlpc_depparser_uni_web_107'])
in_sentences = []
while True:
line = sys.stdin.readline()
if len(line) <= 0:
break
line = line.strip(' \t\n\r')
in_sentences.append(str(line))
if len(in_sentences) < 1000:
continue
m_input = nlpc.depparser_uni_input()
m_input.grain_size = 1
m_input.sentence_segmented = False
m_input.sentences = in_sentences
input_data = sofa.serialize(m_input)
for i in range(5):
try:
ret, output_data = query_agent.call_method(input_data)
break
except Exception as e:
continue
if len(output_data) == 0:
stdout.write('No result' + '\n')
continue
m_output = nlpc.depparser_uni_output()
m_output = sofa.deserialize(output_data, type(m_output))
dep_sentences = m_output.dep_sentences
sent_num = len(dep_sentences)
for i in range(sent_num):
dep_terms = dep_sentences[i].dep_terms
term_num = len(dep_terms)
for j in range(term_num):
if dep_terms[j].lemma.strip() is None:
dep_terms[j].lemma = '_'
if dep_terms[j].cpostag.strip() is None:
dep_terms[j].cpostag = '_'
if dep_terms[j].postag.strip() is None:
dep_terms[j].postag = '_'
if dep_terms[j].ner.strip() is None:
dep_terms[j].ner = '_'
if dep_terms[j].feat.strip() is None:
dep_terms[j].feat = '_'
if dep_terms[j].deprel.strip() is None:
dep_terms[j].deprel = '_'
sys.stdout.write(str(j) + '\t' + dep_terms[j].word + '\t' + dep_terms[j].lemma + '\t' + dep_terms[j].cpostag + '\t' + dep_terms[j].postag + '\t' + dep_terms[j].ner + '\t' + dep_terms[j].feat + '\t' + str(dep_terms[j].head) + '\t' + dep_terms[j].deprel + '\n')
sys.stdout.write('\n')
in_sentences = []
if len(in_sentences) > 0:
m_input = nlpc.depparser_uni_input()
m_input.grain_size = 1
m_input.sentence_segmented = False
m_input.sentences = in_sentences
input_data = sofa.serialize(m_input)
m_input.sentences = in_sentences
input_data = sofa.serialize(m_input)
for i in range(5):
try:
ret, output_data = query_agent.call_method(input_data)
break
except Exception as e:
continue
if len(output_data) == 0:
stdout.write('No result' + '\n')
exit
m_output = nlpc.depparser_uni_output()
m_output = sofa.deserialize(output_data, type(m_output))
dep_sentences = m_output.dep_sentences
sent_num = len(dep_sentences)
for i in range(sent_num):
dep_terms = dep_sentences[i].dep_terms
term_num = len(dep_terms)
for j in range(term_num):
if dep_terms[j].lemma.strip() is None:
dep_terms[j].lemma = '_'
if dep_terms[j].cpostag.strip() is None:
dep_terms[j].cpostag = '_'
if dep_terms[j].postag.strip() is None:
dep_terms[j].postag = '_'
if dep_terms[j].ner.strip() is None:
dep_terms[j].ner = '_'
if dep_terms[j].feat.strip() is None:
dep_terms[j].feat = '_'
if dep_terms[j].deprel.strip() is None:
dep_terms[j].deprel = '_'
sys.stdout.write(str(j) + '\t' + dep_terms[j].word + '\t' + dep_terms[j].lemma + '\t' + dep_terms[j].cpostag + '\t' + dep_terms[j].postag + '\t' + dep_terms[j].ner + '\t' + dep_terms[j].feat + '\t' + str(dep_terms[j].head) + '\t' + dep_terms[j].deprel + '\n')
sys.stdout.write('\n')
in_sentences = []
