Python - WordNet NLTK KeyError

Question

我真的不明白。我正在使用WordNet，并遇到麻烦。我把下面的方法用绳子这样的：

F2F - 进程启动，创建计划数据，创建一个收货，收货创建

def lemmatise(word, pos=NOUN): 
     return WordNetLemmatizer().lemmatize(word, pos) 

这一个调用下一​​个方法：

def lemmatize(self, word, pos=NOUN): 
    lemmas = wordnet._morphy(word, pos) 
    return min(lemmas, key=len) if lemmas else word 

而方法morphy（）是错误表示问题来自的地方（请参阅错误消息）。

def _morphy(self, form, pos): 
    # from jordanbg: 
    # Given an original string x 
    # 1. Apply rules once to the input to get y1, y2, y3, etc. 
    # 2. Return all that are in the database 
    # 3. If there are no matches, keep applying rules until you either 
    # find a match or you can't go any further 
L1687 exceptions = self._exception_map[pos] 
     substitutions = self.MORPHOLOGICAL_SUBSTITUTIONS[pos] 

错误消息

[18/Nov/2016 15:02:57] "GET/HTTP/1.1" 200 4364 
[18/Nov/2016 15:02:57] "GET /static/website/js/animation.js HTTP/1.1" 200 180 
[18/Nov/2016 15:02:57] "GET /static/website/css/animation.css HTTP/1.1" 200 1069 
[18/Nov/2016 15:02:57] "GET /static/website/img/mamegra_pro_thumbnail.png HTTP/1.1" 200 3588 
[18/Nov/2016 15:02:57] "GET /static/website/css/bootstrap.min.css HTTP/1.1" 200 121260 
[18/Nov/2016 15:02:59] "GET /syntactic_matching_final/ HTTP/1.1" 200 5571 
[18/Nov/2016 15:03:02] "GET /semantic_matching_final/ HTTP/1.1" 200 5571 
Internal Server Error: /semantic_matching_final/ 
Traceback (most recent call last): 
    File "C:\Users\Bebop\AppData\Local\Programs\Python\Python35\lib\site-packages\django\core\handlers\exception.py", line 39, in inner 
    response = get_response(request) 
    File "C:\Users\Bebop\AppData\Local\Programs\Python\Python35\lib\site-packages\django\core\handlers\base.py", line 249, in _legacy_get_response 
    response = self._get_response(request) 
    File "C:\Users\Bebop\AppData\Local\Programs\Python\Python35\lib\site-packages\django\core\handlers\base.py", line 187, in _get_response 
    response = self.process_exception_by_middleware(e, request) 
    File "C:\Users\Bebop\AppData\Local\Programs\Python\Python35\lib\site-packages\django\core\handlers\base.py", line 185, in _get_response 
    response = wrapped_callback(request, *callback_args, **callback_kwargs) 
    File "C:\Users\Bebop\OneDrive\Masterarbeit\MamegraPro\MamegraProApp\views.py", line 418, in semantic_matching_final 
    matches = matching.match_optimization('semantic_final', enable_infocontent) #perform syntactic matching and save matches in variable 
    File "C:\Users\Bebop\OneDrive\Masterarbeit\MamegraPro\MamegraProApp\classes\class_matching.py", line 55, in match_optimization 
    scores = {(n1, n2): self.semantic_score_final(n1.name, n2.name, enable_infocontent) if self.semantic_score_final(n1.name, n2.name, enable_infocontent) >= self.minimum_ratio else 0 for n1 in nodes1 for n2 in nodes2} 
    File "C:\Users\Bebop\OneDrive\Masterarbeit\MamegraPro\MamegraProApp\classes\class_matching.py", line 55, in <dictcomp> 
    scores = {(n1, n2): self.semantic_score_final(n1.name, n2.name, enable_infocontent) if self.semantic_score_final(n1.name, n2.name, enable_infocontent) >= self.minimum_ratio else 0 for n1 in nodes1 for n2 in nodes2} 
    File "C:\Users\Bebop\OneDrive\Masterarbeit\MamegraPro\MamegraProApp\classes\class_matching.py", line 557, in semantic_score_final 
    lemmas = self.corpusBase.lemmatise(w1) 
    File "C:\Users\Bebop\OneDrive\Masterarbeit\MamegraPro\MamegraProApp\classes\class_wordnetWrapper.py", line 8, in lemmatise 
    return WordNetLemmatizer().lemmatize(word, pos) 
    File "C:\Users\Bebop\AppData\Local\Programs\Python\Python35\lib\site-packages\nltk\stem\wordnet.py", line 40, in lemmatize 
    lemmas = wordnet._morphy(word, pos) 
    File "C:\Users\Bebop\AppData\Local\Programs\Python\Python35\lib\site-packages\nltk\corpus\reader\wordnet.py", line 1687, in _morphy 
    exceptions = self._exception_map[pos] 
KeyError: 'Created' 
[18/Nov/2016 15:03:11] "POST /semantic_matching_final/ HTTP/1.1" 500 122256 
Not Found: /favicon.ico 
[18/Nov/2016 15:03:12] "GET /favicon.ico HTTP/1.1" 404 4238 

奇怪的是，它随机地切换它引发错误即使是相同的输入字。请帮帮我！

Answer 1

检查以确保您传递的是一个字母而不是较长的字符串。这些可以在源nltk.corpus.reader.wordnet 的常量部分找到{词类常量ADJ，ADJ_SAT，ADV，NOUN，VERB ='a'，'s'，'r'，'n'， 'v'＃}