如何將用戶輸入字符串轉換爲正確的對象類型

Question

我正在使用Python（2.7）以及自然語言工具包（3.2.1）和WordNet。我是很新編程新手。

我正在嘗試編寫一個程序，要求用戶輸入一個單詞，然後打印該單詞的同義詞集，然後詢問用戶要查看哪個同義詞集。

問題是raw_input只接受字符串，所以當我嘗試在用戶輸入上使用方法.lemma_names()時，出現錯誤AttributeError: 'str' object has no attribute 'lemma_names'。

下面是代碼：

from nltk.corpus import wordnet as wn 

w1 = raw_input ("What is the word? ") 

#This prints the synsets for w1, thus showing them what format to use in the next question. 

for synset in wn.synsets(w1): 
    print synset 

#This asks the user to choose the synset of w1 that interests them. 

synset1 = raw_input ("Which sense are you looking for? [Use same format as above]") 

#This prints the lemmas from the synset of interest. 

for x in synset1.lemma_names(): 
    print x 

我的問題是，如何從一個字符串，我可以使用.lemma_names()方法上的同義詞集合型轉換用戶的輸入？

我很抱歉，如果這個問題是如此基本以至於離題。如果是這樣，讓我知道。

Answer 1

試試這個：

from nltk.corpus import wordnet as wn 

w1 = raw_input ("What is the word? ") 

synset_dict = dict() 
for synset in wn.synsets(w1): 
    name = synset.name() 
    synset_dict[name] = synset 
    print name 

synset1 = raw_input ("Which sense are you looking for? [Use same format as above] ") 

if synset1 in synset_dict: 
    synset = synset_dict[synset1] 
    for lemma in synset.lemma_names(): 
     print lemma