我想为我的语言模型计算条件概率分布,但我不能这样做,因为我需要我无法生成的条件频率分布。这是我的代码:
# -*- coding: utf-8 -*-
import io
import nltk
from nltk.util import ngrams
from nltk.tokenize import sent_tokenize
from preprocessor import utf8_to_ascii
with io.open("mypet.txt",'r',encoding='utf8') as utf_file:
file_content = utf_file.read()
ascii_content = utf8_to_ascii(file_content)
sentence_tokenize_list = sent_tokenize(ascii_content)
all_trigrams = []
for sentence in sentence_tokenize_list:
sentence = sentence.rstrip('.!?')
tokens = nltk.re.findall(r"\w+(?:[-']\w+)*|'|[-.(]+|\S\w*", sentence)
trigrams = ngrams(tokens, 3,pad_left=True,pad_right=True,left_pad_symbol='<s>', right_pad_symbol="</s>")
all_trigrams.extend(trigrams)
conditional_frequency_distribution = nltk.ConditionalFreqDist(all_trigrams)
conditional_probability_distribution = nltk.ConditionalProbDist(conditional_frequency_distribution, nltk.MLEProbDist)
for trigram in all_trigrams:
print "{0}: {1}".format(conditional_probability_distribution[trigram[0]].prob(trigram[1]), trigram)
但我收到此错误:
line 23, in <module>
ValueError: too many values to unpack
这是我处理 utf-8 字符的 preprocessor.py 文件:
# -*- coding: utf-8 -*-
import json
def utf8_to_ascii(utf8_text):
with open("utf_to_ascii.json") as data_file:
data = json.load(data_file)
utf_table = data["chars"]
for key, value in utf_table.items():
utf8_text = utf8_text.replace(key, value)
return utf8_text.encode('ascii')
这是我用来将 utf-8 char 替换为 ascii char 的 utf_to_ascii.json 文件:
{
"chars": {
"“":"",
"”":"",
"’":"'",
"—":"-",
"–":"-"
}
}
有人可以建议我如何计算 NLTK 中三元组的条件频率分布?