NLTK——NLTK的正则表达式分词器(nltk.regexp_tokenize)

在《Python自然语言处理》一书中的P121出现来一段利用NLTK自带的正则表达式分词器——nlt.regexp_tokenize,书中代码为:

1 text = 'That U.S.A. poster-print ex-costs-ed $12.40 ... 8% ?  _'
2     pattern = r'''(?x)    # set flag to allow verbose regexps
3         ([A-Z].)+        # abbreviations, e.g. U.S.A.
4        |w+(-w+)*        # words with optional internal hyphens
5        |$?d+(.d+)?%?  # currency and percentages, e.g. $12.40, 82%
6        |...            # ellipsis
7        |(?:[.,;"'?():-_`])  # these are separate tokens; includes ], [
8      '''

其中text变量结尾的“8%”和“_”是我自己加上去的。

预期输出应该是:

1 ['That', 'U.S.A.', 'poster-print', 'ex-costs-ed', '$12.40', '...', '8%', '?', '_']

可实际代码是:

1 [('', '', ''), ('A.', '', ''), ('', '-print', ''), ('', '-ed', ''), ('', '', '.40'), ('', '', ''), ('', '', ''), ('', '', ''), ('', '', '')]

会出现这样的问题是由于nltk.internals.compile_regexp_to_noncapturing()在V3.1版本的NLTK中已经被抛弃(尽管在更早的版本中它仍然可以运行),为此我们把之前定义的pattern稍作修改(参考:https://blog.csdn.net/baimafujinji/article/details/51051505

1 pattern = r'''(?x)    # set flag to allow verbose regexps
2         (?:[A-Z].)+        # abbreviations, e.g. U.S.A.
3        |w+(?:-w+)*        # words with optional internal hyphens
4        |$?d+(?:.d+)?%?  # currency and percentages, e.g. $12.40, 82%
5        #|w+(?:-w+)* 
6        |...            # ellipsis
7        |(?:[.,;"'?():-_`])  # these are separate tokens; includes ], [
8      '''

实际输出结果是:

1 ['That', 'U.S.A.', 'poster-print', 'ex-costs-ed', '$12.40', '...', '8', '?', '_']

我们发现‘8’应该显示成‘8%’才对,后发现将第三行的‘*’去掉或者将第三四行调换位置即可正常显示,修改后代码如下:

1 pattern = r'''(?x)    # set flag to allow verbose regexps
2         (?:[A-Z].)+        # abbreviations, e.g. U.S.A.
3        #|w+(?:-w+)*        # words with optional internal hyphens
4        |$?d+(?:.d+)?%?  # currency and percentages, e.g. $12.40, 82%
5        |w+(?:-w+)* 
6        |...            # ellipsis
7        |(?:[.,;"'?():-_`])  # these are separate tokens; includes ], [
8      '''

此时结果显示正常,所以得出结论就是‘*’影响了它下面的正则表达式中的百分号'%'的匹配。至于为什么就不得而知了。

 

原文地址:https://www.cnblogs.com/LCharles/p/10876017.html