Python-WordNet NLTK关键字错误

我真的不明白。我正在使用WordNet，我遇到了麻烦。我使用如下字符串调用以下方法：

F2F-流程已启动，创建计划数据，创建货物收据，创建货物收据

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

这个调用下一个方法：

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

方法morphy（）是错误的来源（请参阅错误消息）

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

[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_缩略图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/syntatic\u matching\u final/HTTP/1.1”200 5571
[18/Nov/2016 15:03:02]“GET/semantic\u matching\u final/HTTP/1.1”200 5571
内部服务器错误：/semantic\u matching\u final/
回溯（最近一次呼叫最后一次）：
文件“C:\Users\Bebop\AppData\Local\Programs\Python\Python35\lib\site packages\django\core\handlers\exception.py”，第39行，在内部
响应=获取响应（请求）
文件“C:\Users\Bebop\AppData\Local\Programs\Python\Python35\lib\site packages\django\core\handlers\base.py”，第249行，在“legacy\u get\u response”中
响应=自我。获取响应（请求）
文件“C:\Users\Bebop\AppData\Local\Programs\Python\Python35\lib\site packages\django\core\handlers\base.py”，第187行，在get响应中
response=self.process\u异常\u由\u中间件（e，请求）
文件“C:\Users\Bebop\AppData\Local\Programs\Python\Python35\lib\site packages\django\core\handlers\base.py”，第185行，在get响应中
响应=包装的回调（请求，*回调参数，**回调参数）
文件“C:\Users\Bebop\OneDrive\Masterarbeit\MamegraPro\MamegraProApp\views.py”，第418行，语义匹配
matches=matching.match_优化（'semantic_final'，enable_infocontent）#执行语法匹配并将匹配保存在变量中
文件“C:\Users\Bebop\OneDrive\Masterarbeit\MamegraPro\MamegraProApp\classes\class\u matching.py”，第55行，匹配优化
分数={（n1，n2）：self.semantic_分数_final（n1.name，n2.name，enable_infocontent）如果self.semantic_分数_final（n1.name，n2.name，enable_infocontent）>=self.minimum_ratio其他0表示节点1中的n1表示节点2中的n2}
文件“C:\Users\Bebop\OneDrive\Masterarbeit\MamegraPro\MamegraProApp\classes\class\u matching.py”，第55行，在
分数={（n1，n2）：self.semantic_分数_final（n1.name，n2.name，enable_infocontent）如果self.semantic_分数_final（n1.name，n2.name，enable_infocontent）>=self.minimum_ratio其他0表示节点1中的n1表示节点2中的n2}
文件“C:\Users\Bebop\OneDrive\Masterarbeit\MamegraPro\MamegraProApp\classes\class\u matching.py”，第557行，在semantic\u score\u final中
引理=self.corpusBase.lemmasise（w1）
文件“C:\Users\Bebop\OneDrive\Masterarbeit\MamegraPro\MamegraProApp\classes\class\u wordnetWrapper.py”，lemmatise中的第8行
返回WordNetLemmatizer（）.lemmatize（word，pos）
文件“C:\Users\Bebop\AppData\Local\Programs\Python\Python35\lib\site packages\nltk\stem\wordnet.py”，第40行，在lemmatize中
引理=wordnet.\u词形（单词，词性）
文件“C:\Users\Bebop\AppData\Local\Programs\Python\Python35\lib\site packages\nltk\corpus\reader\wordnet.py”，第1687行，在
异常=自身。异常映射[pos]
KeyError:“已创建”
[18/Nov/2016 15:03:11]“POST/semantic\u matching\u final/HTTP/1.1”500 122256
未找到：/favicon.ico
[18/Nov/2016 15:03:12]“GET/favicon.ico HTTP/1.1”404 4238

---

奇怪的是，即使输入相同，它也会在抛出错误的地方随机切换单词。请帮帮我

检查以确保传递的是一个字母，而不是更长的字符串。这些可以在源nltk.corpus.reader.wordnet的常量部分找到

---

{词性常数ADJ，ADJ#u SAT，ADV，名词，动词='a'，'s'，'r'，'n'，'v'#}

这并没有帮助我解决这个问题，但由于你的帮助，我发现了主要问题。非常感谢。

[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