在pyspark dataframe上使用POS标签的nltk wordnet词汇化

from pyspark.sql.functions import udf
from nltk.corpus import wordnet
from nltk.stem import WordNetLemmatizer

def lemmatize_word(word, pos_tag):
    # 初始化WordNetLemmatizer对象
    lemmatizer = WordNetLemmatizer()
    
    # 将POS标签转换为WordNet中的标签格式
    if pos_tag.startswith('N'):
        pos = wordnet.NOUN
    elif pos_tag.startswith('V'):
        pos = wordnet.VERB
    elif pos_tag.startswith('J'):
        pos = wordnet.ADJ
    elif pos_tag.startswith('R'):
        pos = wordnet.ADV
    else:
        pos = wordnet.NOUN
    
    # 调用WordNetLemmatizer对象的lemmatize方法进行词汇化
    return lemmatizer.lemmatize(word, pos)

lemmatize_udf = udf(lemmatize_word)

# 假设df为包含文本的pyspark dataframe，'text'列为待处理的文本列，'pos_tag'列为POS标签列
df = df.withColumn('lemmatized_text', lemmatize_udf(df['text'], df['pos_tag']))