Python正则表达式nltk网站提取 [英] Python Regular Expression nltk website extraction
问题描述
我以前从未处理过正则表达式,我正尝试使用Python和NLTK预处理一些原始文本. 当我尝试使用:标记文档时:
Hi I have never had to deal with regex before and I'm trying to preprocess some raw text with Python and NLTK. when I tried to tokenize the document using :
tokens = nltk.regexp_tokenize(corpus, sentence_re)
sentence_re = r'''(?x) # set flag to allow verbose regexps
([A-Z])(\.[A-Z])+\.? # abbreviations, e.g. U.S.A.
| \w+(-\w+)* # words with optional internal hyphens
| \$?\d+(\.\d+)?%? # currency and percentages, e.g. $12.40, 82%
| \#?\w+|\@?\w+ # hashtags and @ signs
| \.\.\. # ellipsis
| [][.,;"'?()-_`] # these are separate tokens
| ?:http://|www.)[^"\' ]+ # websites
'''
它不能将所有网站都当作一个令牌:
its not able to take all of the website as one single token:
print toks[:50]
['on', '#Seamonkey', '(', 'SM', ')', '-', 'I', 'had', 'a', 'short', 'chirp', 'exchange', 'with', '@angie1234p', 'at', 'the', '18thDec', ';', 'btw', 'SM', 'is', 'faster', 'has', 'also', 'an', 'agile', '...', '1', '/', '2', "'", '...', 'user', 'community', '-', 'http', ':', '/', '/', 'bit', '.', 'ly', '/', 'XnF5', '+', 'ICR', 'http', ':', '/', '/']
非常感谢您的帮助.非常感谢!
any help is greatly appreicated. Thanks so much!
-弗洛里
推荐答案
在此令牌生成器中,RegularExpressions用于指定要从文本中提取的令牌的外观. 我有点困惑您使用了上面的许多正则表达式中的哪一个,但是对于非空白标记的非常简单的标记化,您可以使用:
In this tokenizer RegularExpressions are used to specify how the Tokens you want to extract from the text can look like. I'm a bit confused which of the many regular expressions above you used, but for a very simple tokenization to non-whitespace tokens you could use:
>>> corpus = "this is a sentence. and another sentence. my homepage is http://test.com"
>>> nltk.regexp_tokenize(corpus, r"\S+")
['this', 'is', 'a', 'sentence.', 'and', 'another', 'sentence.', 'my', 'homepage', 'is', 'http://test.com']
等效于:
>>> corpus.split()
['this', 'is', 'a', 'sentence.', 'and', 'another', 'sentence.', 'my', 'homepage', 'is', 'http://test.com']
另一种方法可能是使用nltk函数send_tokenize()和nltk.word_tokenize():
another approach could be using the nltk functions sent_tokenize() and nltk.word_tokenize():
>>> sentences = nltk.sent_tokenize(corpus)
>>> sentences
['this is a sentence.', 'and another sentence.', 'my homepage is http://test.com']
>>> for sentence in sentences:
print nltk.word_tokenize(sentence)
['this', 'is', 'a', 'sentence', '.']
['and', 'another', 'sentence', '.']
['my', 'homepage', 'is', 'http', ':', '//test.com']
尽管如果您的文本包含很多网站网址,这可能不是最佳选择.可以在此处.
though if your text contains lots of website-urls this might not be the best choice. information about the different tokenizers in the NLTK can be found here.
如果您只想从语料库中提取URL,则可以使用如下正则表达式:
if you just want to extract URLs from the corpus you could use a regular expression like this:
nltk.regexp_tokenize(corpus, r'(http://|https://|www.)[^"\' ]+')
希望这会有所帮助.如果这不是您想要的答案,请尝试更精确地解释您想要做的事情以及您想要令牌的精确程度(例如,您希望拥有的示例输入/输出),我们可以为您提供帮助找到正确的正则表达式.
Hope this helps. If this was not the answer you were looking for, please try to explain a bit more precisely what you want to do and how exactely you want your tokens look like (e.g. an example input/output you would like to have) and we can help finding the right regular expression.
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