def review_model_predict_entities(model_predict_entities):
word_tag_map = POSTokenizer().word_tag_tab
idf_freq = TFIDF().idf_freq
reviewed_entities = defaultdict(list)
for ent_type, ent_and_sent_list in model_predict_entities.items():
for ent, sent in ent_and_sent_list:
start = sent.lower().find(ent)
if start == -1:
continue
start += 1
end = start + len(ent) - 1
tokens = jieba.lcut(sent)
offset = 0
selected_tokens = []
for token in tokens:
offset += len(token)
if offset >= start:
selected_tokens.append(token)
if offset >= end:
break
fixed_entity = ''.join(selected_tokens)
fixed_entity = re.sub(r'\d*\.?\d+%$', '', fixed_entity)
if ent_type == '人物':
if len(fixed_entity) >= 10:
continue
if len(fixed_entity) <= 1:
continue
if re.findall(r'^\d+$', fixed_entity):
continue
if word_tag_map.get(fixed_entity,
'') == 'v' and idf_freq[fixed_entity] < 7:
continue
reviewed_entities[ent_type].append(fixed_entity)
return reviewed_entities
class Jieba(object):
def __init__(self, config):
self.config = config
self.dt = POSTokenizer()
def load_dict(self):
self.dict = []
try:
with open(self.config.get("word_dict", None), "r") as frobj:
for line in frobj:
content = line.strip().split("\t")[0]
self.dict.append(content)
except:
raise ValueError("Not existed word piece dict")
def load_model(self):
for word in self.dict:
self.dt.add_word(word)
def build_word_id(self):
self.word2id, self.id2word = {}, {}
for index, word in enumerate(self.dict):
self.word2id[word] = index
self.id2word[index] = word
def add_extra_word(self,
extra_lst=[
"[PAD]", "[UNK]", "[CLS]", "[SEP]", "[MASK]"
]):
extra_lst = extra_lst if extra_lst else self.config.get(
"extra_lst", [])
if len(extra_lst) >= 1:
for word in extra_lst:
if word in self.dict:
self.dict.remove(word)
self.dict = extra_lst + self.dict
def train_model(self, train_config=None):
config = train_config if train_config else self.config
self.dict = []
try:
with open(config.get("word_dict", None)) as frobj:
for line in frobj:
content = line.strip().split("\t")[0]
self.dict.append(content)
except:
raise ValueError(" not existed word dict")
def tokenize(self, text):
tokenized_text = self.dt.lcut(text)
return [list(word)[0] for word in tokenized_text]
def convert_tokens_to_ids(self, text, unk="[UNK]"):
tokenized_text = self.tokenize(text)
token_id_lst = [
self.word2id.get(word, self.word2id[unk])
for word in tokenized_text
]
return token_id_lst
def __init__(self):
self.token = jieba.Tokenizer()
file = [
x.path for x in os.scandir(config.JIEBA_DICT_PATH)
if x.path.endswith("txt")
]
for fp in file:
self.token.load_userdict(fp)
self.pos_token = POSTokenizer(self.token)
class Jieba_CHAR(object):
def __init__(self, config):
print("----------using naive cut tool---------")
self.config = config
self.dt = POSTokenizer()
def load_vocab(self, vocab_lst=None):
try:
self.word2id = {}
for index, word in enumerate(vocab_lst):
self.dt.add_word(word, 1e5)
self.word2id[word] = index
print("==total vocab==", len(self.word2id))
except:
print("==not included word list==")
def tokenize(self, text):
out = []
char_pattern = re.compile(u"[\u4e00-\u9fa5]+")
word_list = list(self.dt.lcut("".join(text.split())))
for word in word_list:
word = list(word)
char_cn = char_pattern.findall(word[0])
if len(char_cn) >= 1:
for item in word[0]:
if len(item) >= 1:
out.append(item)
else:
if len(word[0]) >= 1:
out.append(word[0])
return out
def convert_tokens_to_ids(self, token_lst, max_length):
token_id_lst = [self.word2id["<pad>"] for _ in range(max_length)]
for index, word in enumerate(token_lst[0:max_length]):
if word in self.word2id:
token_id_lst[index] = self.word2id[word]
else:
token_id_lst[index] = self.word2id["<unk>"]
return token_id_lst
def covert_tokens_to_char_ids(self, token_lst, max_length, char_len=5):
char_id_lst = [[self.word2id["<pad>"] for _ in range(char_len)] for _ in range(max_length)]
for index, word in enumerate(token_lst[0:max_length]):
for char_index, char in enumerate(word[0:char_len]):
if char in self.word2id:
char_id_lst[index][char_index] = self.word2id[char]
else:
char_id_lst[index][char_index] = self.word2id["<unk>"]
return char_id_lst
class jieba_api(object):
def __init__(self):
print("----------using jieba cut tool---------")
def init_config(self, config):
self.config = config
self.dt = POSTokenizer()
def build_tool(self):
dict_path = self.config.get("user_dict", None)
if dict_path is not None:
import codecs
with codecs.open(dict_path, "r", "utf-8") as frobj:
lines = frobj.read().splitlines()
for line in lines:
content = line.split("\t")
self.dt.add_word(content[0], int(content[1]), content[2])
def cut(self, text):
words = list(self.dt.cut(text))
# print(words, " ".join([word for word in words if len(word) >= 1]))
return " ".join([word for word in words if len(word) >= 1])
class TextTool:
def __init__(self):
self.token = jieba.Tokenizer()
file = [
x.path for x in os.scandir(config.JIEBA_DICT_PATH)
if x.path.endswith("txt")
]
for fp in file:
self.token.load_userdict(fp)
self.pos_token = POSTokenizer(self.token)
def lcut(self, query):
return self.token.lcut(query)
def pos_lcut(self, query):
return self.pos_token.lcut(query)
def import_jieba_posseg(dt=None):
from jieba.posseg import POSTokenizer
dt_pos = POSTokenizer(tokenizer=dt)
return dt_pos
def __init__(self, config):
self.config = config
self.dt = POSTokenizer()
def jieba_wrap_init(): global posseg_tok posseg_tok = POSTokenizer(jieba.dt)
def __init__(self, config):
print("----------using naive cut tool---------")
self.config = config
self.dt = POSTokenizer()
def init_config(self, config):
self.config = config
self.dt = POSTokenizer()
self.cut_flag = False
self.word_type = []
self.dt.add_word("<SEG>", 10000)
class cut_tool_api(object):
def __init__(self):
print("----------using naive cut tool---------")
def init_config(self, config):
self.config = config
self.dt = POSTokenizer()
self.cut_flag = False
self.word_type = []
self.dt.add_word("<SEG>", 10000)
def build_tool(self):
import codecs
self.word_type = []
try:
dict_path = self.config.get("user_dict", None)
with codecs.open(dict_path, "r", "utf-8") as frobj:
lines = frobj.read().splitlines()
for line in lines:
content = line.split("\t")
try:
self.dt.add_word(content[0], int(content[1]),
content[2])
self.word_type.append(content[2])
except:
continue
self.dt.add_word("$$", 100000, "<split_symbol>")
print("====succeeded in loading dictionary====", dict_path)
self.word_type = list(set(self.word_type))
self.word_type = [
item for item in self.word_type if len(item) >= 1
]
self.word_type.append("$$")
except:
self.cut_flag = False
def cut(self, text, target=None):
out = []
char_pattern = re.compile(u"[\u4e00-\u9fa5]+")
word_list = list(self.dt.lcut("".join(text.split())))
for word in word_list:
word = list(word)
if len(word[0]) == 0:
continue
if self.cut_flag:
if word[1] in self.word_type:
if target:
if word[0] == target:
out.append("<target>")
else:
out.append(word[1])
else:
out.append(word[0])
else:
char_cn = char_pattern.findall(word[0])
if len(char_cn) >= 1:
for item in word[0]:
if len(item) >= 1:
out.append(item)
else:
if len(word[0]) >= 1:
out.append(word[0])
else:
char_cn = char_pattern.findall(word[0])
if len(char_cn) >= 1:
for item in word[0]:
if len(item) >= 1:
out.append(item)
else:
if len(word[0]) >= 1:
out.append(word[0])
return " ".join(out)
def init_config(self, config):
self.config = config
self.dt = POSTokenizer()