如何通过nltk同义词集迭代每个单词，并将拼写错误的单词存储在单独的列表中

Question

我试图通过NLTK wordnet synset函数获取带有消息的文本文件并迭代每个单词。我想这样做是因为我想创建一个拼写错误的单词列表。例如，如果我这样做:

wn.synsets('dog')

我得到输出:

[Synset('dog.n.01'),
 Synset('frump.n.01'),
 Synset('dog.n.03'),
 Synset('cad.n.01'),
 Synset('frank.n.02'),
 Synset('pawl.n.01'),
 Synset('andiron.n.01'),
 Synset('chase.v.01')]

现在如果单词拼写错误，像这样:

wn.synsets('doeg')

我得到输出:

[]

如果我返回一个空列表，我想将拼写错误的单词保存在另一个列表中，像这样，同时继续遍历文件的其余部分:

mispelled_words = ['doeg']

我不知道如何做到这一点，下面是我的代码，我需要在变量"chat_message_tokenize"之后进行迭代。名称路径是我要删除的单词:

import nltk
import csv
from nltk.tag import pos_tag
from nltk.corpus import wordnet as wn
from nltk.stem.snowball import SnowballStemmer

def text_function():
    #nltk.download('punkt')
    #nltk.download('averaged_perceptron_tagger')
    # Read in chat messages and names files
    chat_path = 'filepath.csv'
    try:
        with open(chat_path) as infile:
            chat_messages = infile.read()
    except Exception as error:
        print(error)
        return
    name_path = 'filepath.txt'
    try:
        with open(names_path) as infile:
            names = infile.read()
    except Exception as error:
        print(error)
        return
    chat_messages = chat_messages.split('Chats:')[1].strip()
    names = names.split('Name:')[1].strip().lower()
    chat_messages_tokenized = nltk.word_tokenize(chat_messages)
    names_tokenized = nltk.word_tokenize(names)
    # adding part of speech(pos) tag and dropping proper nouns
    pos_drop = pos_tag(chat_messages_tokenized)
    chat_messages_tokenized = [SnowballStemmer('english').stem(word.lower()) for word, pos in pos_drop if pos != 'NNP' and word not in names_tokenized]
    for chat_messages_tokenized 
    if not wn.synset(chat_messages_tokenized):
        print('empty list')
if __name__ == '__main__':
    text_function()    
#    for s in wn.synsets('dog'):
#          lemmas = s.lemmas()
#    for l in lemmas:
#          if l.name() == stemmer:
#              print (l.synset())

    csv_path ='OutputFilePath.csv'
    try:
        with open(csv_path, 'w') as outfile:
            writer = csv.writer(outfile)
            for word in chat_messages_tokenized:
                writer.writerow([word])
    except Exception as error:
        print(error)
        return

if __name__ == '__main__':
    text_function()

提前谢谢你。

Answer 1

在您的解释中已经有了伪代码，您可以按照您解释的那样编写它，如下所示:

misspelled_words = []                 # The list to store misspelled words
for word in chat_messages_tokenized:  # loop through each word
    if not wn.synset(word):           # if there is no synset for this word
        misspelled_words.append(word) # add it to misspelled word list
print(misspelled_words)