有人有针对NLTK的分类XML语料库阅读器吗？

Question

有人为NLTK编写过分类XML语料库阅读器吗？在

我在用带注释的纽约时报语料库。它是一个XML语料库。 我可以用XMLCorpusReader读取文件，但我想使用NLTK的一些分类功能。有一个nice tutorial用于子类化NLTK读取器。我可以继续写这篇文章，但我希望如果有人已经写了这篇文章，我希望能节省一些时间。在

如果没有，我就把我写的东西贴出来。在

Answer 1

很抱歉，但是把它作为一个新问题发布是我发现讨论这个代码的唯一方法。我还在使用words（）方法尝试使用categories时发现了一个小错误。这里：https://github.com/nltk/nltk/issues/250#issuecomment-5273102

你比我先解决这个问题了吗？另外，您是否对其进行了进一步的修改，以使类别发挥作用？我的电子邮件在我的个人资料页，如果你想谈论它，所以：-）

Answer 2

这是一个用于NLTK的分类XML语料库阅读器。它基于this tutorial. 这使您可以在XML语料库上使用NLTK的基于类别的特性，如《纽约时报》带注释的语料库。在

把这个文件叫做CategorizedXMLCorpusReader.py并将其导入为：

import imp                                                                                                                                                                                                                     
CatXMLReader = imp.load_source('CategorizedXMLCorpusReader','PATH_TO_THIS_FILE/CategorizedXMLCorpusReader.py')  

然后您可以像其他NLTK阅读器一样使用它。例如

^{pr2}$

我仍在考虑NLTK，所以欢迎任何更正或建议。在

# Categorized XML Corpus Reader                                                                                                                                                                                                  

from nltk.corpus.reader import CategorizedCorpusReader, XMLCorpusReader
class CategorizedXMLCorpusReader(CategorizedCorpusReader, XMLCorpusReader):
    def __init__(self, *args, **kwargs):
        CategorizedCorpusReader.__init__(self, kwargs)
        XMLCorpusReader.__init__(self, *args, **kwargs)
    def _resolve(self, fileids, categories):
        if fileids is not None and categories is not None:
            raise ValueError('Specify fileids or categories, not both')
        if categories is not None:
            return self.fileids(categories)
        else:
            return fileids

        # All of the following methods call the corresponding function in ChunkedCorpusReader                                                                                                                                    
        # with the value returned from _resolve(). We'll start with the plain text methods.                                                                                                                                      
    def raw(self, fileids=None, categories=None):
        return XMLCorpusReader.raw(self, self._resolve(fileids, categories))

    def words(self, fileids=None, categories=None):
        #return CategorizedCorpusReader.words(self, self._resolve(fileids, categories))                                                                                                                                          
        # Can I just concat words over each file in a file list?                                                                                                                                                                 
        words=[]
        fileids = self._resolve(fileids, categories)
        # XMLCorpusReader.words works on one file at a time. Concatenate them here.                                                                                                                                              
        for fileid in fileids:
            words+=XMLCorpusReader.words(self, fileid)
        return words

    # This returns a string of the text of the XML docs without any markup                                                                                                                                                       
    def text(self, fileids=None, categories=None):
        fileids = self._resolve(fileids, categories)
        text = ""
        for fileid in fileids:
            for i in self.xml(fileid).getiterator():
                if i.text:
                    text += i.text
        return text

    # This returns all text for a specified xml field                                                                                                                                                                            
    def fieldtext(self, fileids=None, categories=None):
        # NEEDS TO BE WRITTEN                                                                                                                                                                                                    
        return

    def sents(self, fileids=None, categories=None):
        #return CategorizedCorpusReader.sents(self, self._resolve(fileids, categories))                                                                                                                                          
        text = self.words(fileids, categories)
        sents=nltk.PunktSentenceTokenizer().tokenize(text)
        return sents

    def paras(self, fileids=None, categories=None):
        return CategorizedCorpusReader.paras(self, self._resolve(fileids, categories))