如何根据多个标签对语料库中的单词进行排序？Python，nltk

import nltk
from nltk.corpus import stopwords
from nltk.tokenize import word_tokenize
from nltk.stem import WordNetLemmatizer
from collections import defaultdict

corpus = "这是一个示例语料库，包含一些单词。"
labels = {"标签1": ["单词1", "单词2"], "标签2": ["单词3", "单词4"]}

# 分词
tokens = word_tokenize(corpus)

# 去除停用词
stop_words = set(stopwords.words("english"))
filtered_tokens = [token for token in tokens if token.lower() not in stop_words]

# 词形还原
lemmatizer = WordNetLemmatizer()
lemmatized_tokens = [lemmatizer.lemmatize(token) for token in filtered_tokens]

word_counts = defaultdict(lambda: defaultdict(int))

for word in lemmatized_tokens:
    for label, label_words in labels.items():
        if word in label_words:
            word_counts[word][label] += 1

sorted_words = sorted(word_counts.keys(), key=lambda w: sum(word_counts[w].values()), reverse=True)

for word in sorted_words:
    label_counts = word_counts[word]
    sorted_labels = sorted(label_counts.keys(), key=lambda l: label_counts[l], reverse=True)
    print(f"单词 '{word}' 出现次数最多的标签是 '{sorted_labels[0]}'")