python之元组没有属性 'isdigit'

我需要使用 NLTK 模块进行一些文字处理，但出现此错误: AttributeError: 'tuple' 对象没有属性 'isdigit'

有人知道如何处理这个错误吗？

Traceback (most recent call last): 
  File "preprocessing-edit.py", line 36, in <module> 
    postoks = nltk.tag.pos_tag(tok) 
NameError: name 'tok' is not defined 
 
PS C:\Users\moham\Desktop\Presentation> python preprocessing-edit.py 
Traceback (most recent call last): 
  File "preprocessing-edit.py", line 37, in <module> 
    postoks = nltk.tag.pos_tag(tok) 
  File "c:\python34\lib\site-packages\nltk-3.1-py3.4.egg\nltk\tag\__init__.py", line 111, in pos_tag 
    return _pos_tag(tokens, tagset, tagger) 
  File "c:\python34\lib\site-packages\nltk-3.1-py3.4.egg\nltk\tag\__init__.py", line 82, in _pos_tag 
    tagged_tokens = tagger.tag(tokens) 
  File "c:\python34\lib\site-packages\nltk-3.1-py3.4.egg\nltk\tag\perceptron.py", line 153, in tag 
    context = self.START + [self.normalize(w) for w in tokens] + self.END 
  File "c:\python34\lib\site-packages\nltk-3.1-py3.4.egg\nltk\tag\perceptron.py", line 153, in <listcomp> 
    context = self.START + [self.normalize(w) for w in tokens] + self.END 
  File "c:\python34\lib\site-packages\nltk-3.1-py3.4.egg\nltk\tag\perceptron.py", line 228, in normalize 
    elif word.isdigit() and len(word) == 4: 
AttributeError: 'tuple' object has no attribute 'isdigit' 

import nltk 
 
with open ("SHORT-LIST.txt", "r",encoding='utf8') as myfile: 
    text =  (myfile.read().replace('\n', '')) 
 
#text = "program managment is complicated issue for human workers" 
 
# Used when tokenizing words 
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% 
    | \.\.\.                # ellipsis 
    | [][.,;"'?():-_`]      # these are separate tokens 
''' 
 
lemmatizer = nltk.WordNetLemmatizer() 
stemmer = nltk.stem.porter.PorterStemmer() 
 
 
grammar = r""" 
    NBAR: 
        {<NN.*|JJ>*<NN.*>}  # Nouns and Adjectives, terminated with Nouns 
 
    NP: 
        {<NBAR>} 
        {<NBAR><IN><NBAR>}  # Above, connected with in/of/etc... 
""" 
chunker = nltk.RegexpParser(grammar) 
 
tok = nltk.regexp_tokenize(text, sentence_re) 
 
postoks = nltk.tag.pos_tag(tok) 
 
#print (postoks) 
 
tree = chunker.parse(postoks) 
 
from nltk.corpus import stopwords 
stopwords = stopwords.words('english') 
 
 
def leaves(tree): 
    """Finds NP (nounphrase) leaf nodes of a chunk tree.""" 
    for subtree in tree.subtrees(filter = lambda t: t.label()=='NP'): 
        yield subtree.leaves() 
 
def normalise(word): 
    """Normalises words to lowercase and stems and lemmatizes it.""" 
    word = word.lower() 
    word = stemmer.stem_word(word) 
    word = lemmatizer.lemmatize(word) 
    return word 
 
def acceptable_word(word): 
    """Checks conditions for acceptable word: length, stopword.""" 
    accepted = bool(2 <= len(word) <= 40 
        and word.lower() not in stopwords) 
    return accepted 
 
 
def get_terms(tree): 
    for leaf in leaves(tree): 
        term = [ normalise(w) for w,t in leaf if acceptable_word(w) ] 
        yield term 
 
terms = get_terms(tree) 
 
 
with open("results.txt", "w+") as logfile: 
    for term in terms:  
        for word in term: 
            result = word 
            logfile.write("%s\n" % str(word)) 
#           print (word), 
#       (print) 
 
logfile.close()  

请您参考如下方法:

另一种简单的方法是更改​​这部分:

tok = nltk.regexp_tokenize(text, sentence_re) 
postoks = nltk.tag.pos_tag(tok) 

并将其替换为 nltk 标准单词分词器:

toks = nltk.word_tokenize(text) 
postoks = nltk.tag.pos_tag(toks) 

从理论上讲，性能和结果应该没有太大差异。