如何在python中使用nltk从文本文件中提取姓氏

Question

import re
import nltk
from nltk.corpus import stopwords
stop = stopwords.words('english')
from nltk.corpus import wordnet

inputfile = open('file.txt', 'r')
String= inputfile.read()


def last_name(resume_text):
  tokenized_sentences = nltk.sent_tokenize(resume_text)
  a_list=[]
  for sentence in tokenized_sentences:
      a_list=(sentence.split())
      s1=a_list[1:]
      sentence1=''.join(s1)
      tokenized_sentences = nltk.sent_tokenize(sentence1)
      for sentence in tokenized_sentences:
          for chunk in nltk.ne_chunk(nltk.pos_tag(nltk.word_tokenize(sentence), tagset='universal')):
            if hasattr(chunk, 'label') and chunk.label() == 'PERSON':
              chunk = chunk[0]
            (name, tag) = chunk
            if tag == 'NOUN':
              return name
if __name__ == '__main__':
    lastname= last_name(String)
print(lastname)

我想从简历中提取姓氏。它正确返回第一个名称，但第二个名称错误。

我该如何解决这个问题？