替换python

时间:2017-03-25 15:11:08

标签: python nlp textblob

我正在使用python来清理给定的句子。假设我的句子是:

What's the best way to ensure this?

我想转换:

What's -> What is

类似地,

 must've -> must have

此外,动词为原始形式,

told -> tell

单数形式复数,等等。

我正在探索textblob。但并非以上所有都可以使用它。

4 个答案:

答案 0 :(得分:8)

对于第一个问题,没有一个直接模块为你做这个,所以你必须建立自己的,首先你需要一个像这样的收缩字典:

contractions = {
"ain't": "am not / are not",
"aren't": "are not / am not",
"can't": "cannot",
"can't've": "cannot have",
"'cause": "because",
"could've": "could have",
"couldn't": "could not",
"couldn't've": "could not have",
"didn't": "did not",
"doesn't": "does not",
"don't": "do not",
"hadn't": "had not",
"hadn't've": "had not have",
"hasn't": "has not",
"haven't": "have not",
"he'd": "he had / he would",
"he'd've": "he would have",
"he'll": "he shall / he will",
"he'll've": "he shall have / he will have",
"he's": "he has / he is",
"how'd": "how did",
"how'd'y": "how do you",
"how'll": "how will",
"how's": "how has / how is",
"i'd": "I had / I would",
"i'd've": "I would have",
"i'll": "I shall / I will",
"i'll've": "I shall have / I will have",
"i'm": "I am",
"i've": "I have",
"isn't": "is not",
"it'd": "it had / it would",
"it'd've": "it would have",
"it'll": "it shall / it will",
"it'll've": "it shall have / it will have",
"it's": "it has / it is",
"let's": "let us",
"ma'am": "madam",
"mayn't": "may not",
"might've": "might have",
"mightn't": "might not",
"mightn't've": "might not have",
"must've": "must have",
"mustn't": "must not",
"mustn't've": "must not have",
"needn't": "need not",
"needn't've": "need not have",
"o'clock": "of the clock",
"oughtn't": "ought not",
"oughtn't've": "ought not have",
"shan't": "shall not",
"sha'n't": "shall not",
"shan't've": "shall not have",
"she'd": "she had / she would",
"she'd've": "she would have",
"she'll": "she shall / she will",
"she'll've": "she shall have / she will have",
"she's": "she has / she is",
"should've": "should have",
"shouldn't": "should not",
"shouldn't've": "should not have",
"so've": "so have",
"so's": "so as / so is",
"that'd": "that would / that had",
"that'd've": "that would have",
"that's": "that has / that is",
"there'd": "there had / there would",
"there'd've": "there would have",
"there's": "there has / there is",
"they'd": "they had / they would",
"they'd've": "they would have",
"they'll": "they shall / they will",
"they'll've": "they shall have / they will have",
"they're": "they are",
"they've": "they have",
"to've": "to have",
"wasn't": "was not",
"we'd": "we had / we would",
"we'd've": "we would have",
"we'll": "we will",
"we'll've": "we will have",
"we're": "we are",
"we've": "we have",
"weren't": "were not",
"what'll": "what shall / what will",
"what'll've": "what shall have / what will have",
"what're": "what are",
"what's": "what has / what is",
"what've": "what have",
"when's": "when has / when is",
"when've": "when have",
"where'd": "where did",
"where's": "where has / where is",
"where've": "where have",
"who'll": "who shall / who will",
"who'll've": "who shall have / who will have",
"who's": "who has / who is",
"who've": "who have",
"why's": "why has / why is",
"why've": "why have",
"will've": "will have",
"won't": "will not",
"won't've": "will not have",
"would've": "would have",
"wouldn't": "would not",
"wouldn't've": "would not have",
"y'all": "you all",
"y'all'd": "you all would",
"y'all'd've": "you all would have",
"y'all're": "you all are",
"y'all've": "you all have",
"you'd": "you had / you would",
"you'd've": "you would have",
"you'll": "you shall / you will",
"you'll've": "you shall have / you will have",
"you're": "you are",
"you've": "you have"
}

然后编写一些代码来根据字典修改文本,如下所示:

text="What's the best way to ensure this?"
for word in text.split():
    if word.lower() in contractions:
        text = text.replace(word, contractions[word.lower()])
print(text)

关于改变动词时态的第二个问题,nodebox's linguistics library非常受欢迎,强烈推荐用于此类任务。在downloading their zip file之后,解压缩并将其复制到python的site-package目录。完成后,你可以这样写:

import en
for word in text.split():
    if en.is_verb(word.lower()):
        text = text.replace(word, en.verb.present(word.lower()))
print text

注意:此库仅适用于Python 2,因为它尚不支持python 3。

答案 1 :(得分:2)

上面的答案将非常有效,并且可能更适合模糊的收缩(尽管我认为没有那么多含糊不清的案例)。我会使用更易读,更易于维护的东西:

import re

def decontracted(phrase):
    # specific
    phrase = re.sub(r"won\'t", "will not", phrase)
    phrase = re.sub(r"can\'t", "can not", phrase)

    # general
    phrase = re.sub(r"n\'t", " not", phrase)
    phrase = re.sub(r"\'re", " are", phrase)
    phrase = re.sub(r"\'s", " is", phrase)
    phrase = re.sub(r"\'d", " would", phrase)
    phrase = re.sub(r"\'ll", " will", phrase)
    phrase = re.sub(r"\'t", " not", phrase)
    phrase = re.sub(r"\'ve", " have", phrase)
    phrase = re.sub(r"\'m", " am", phrase)
    return phrase


test = "Hey I'm Yann, how're you and how's it going ? That's interesting: I'd love to hear more about it."
print(decontracted(test))
# Hey I am Yann, how are you and how is it going ? That is interesting: I would love to hear more about it.

虽然可能会有一些我没想到的缺陷。

答案 2 :(得分:1)

如果您想自己滚动,可以将其用于收缩映射:

http://alicebot.blogspot.com/2009/03/english-contractions-and-expansions.html

这是动词替换:

http://www.lexically.net/downloads/BNC_wordlists/e_lemma.txt

对于后者,您可能希望生成一个反向字典,将所有共轭形式映射到它们的原始形式(可能要记住可能存在模糊形式,因此请务必检查这些形式并正确处理它们。) / p>

答案 3 :(得分:0)

这可能不适合您的特定解决方案,但(对于一般知识)有一个很棒的开源软件库,名为 Spacy。在类似情况下,它使生活更轻松。演示:

texts = ["what's", "must've", "told"]

for text in texts:
   doc = nlp(text)
   lemmatized_text = ' '.join([token.lemma_ for token in doc])
   print(lemmatized_text)

输出:

what be
must have
tell
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