python – NLTK:如何遍历名词短语以返回字符串列表?

前端之家收集整理的这篇文章主要介绍了python – NLTK:如何遍历名词短语以返回字符串列表?前端之家小编觉得挺不错的,现在分享给大家,也给大家做个参考。
在NLTK中,如何遍历已解析的句子以返回名词短语字符串列表?

我有两个目标:
(1)创建名词短语列表,而不是使用’traverse()’方法打印它们.我目前使用StringIO来记录现有traverse()方法输出.这不是一个可接受的解决方案.
(2)解析名词短语字符串,以便:'(NP Michael / NNP Jackson / NNP)成为’Michael Jackson’.在NLTK中有解除解析的方法吗?

NLTK文档建议使用traverse()来查看名词短语,但是如何在这个递归方法中捕获’t’,以便生成一个字符串名词短语列表?

from nltk.tag import pos_tag

def traverse(t):
  try:
      t.label()
  except AttributeError:
      return
  else:
      if t.label() == 'NP': print(t)  # or do something else
      else:
          for child in t: 
              traverse(child)

def nounPhrase(tagged_sent):
    # Tag sentence for part of speech
    tagged_sent = pos_tag(sentence.split())  # List of tuples with [(Word,PartOfSpeech)]
    # Define several tag patterns
    grammar = r"""
      NP: {<DT|PP\$>?<JJ>*<NN>}   # chunk determiner/possessive,adjectives and noun
      {<NNP>+}                # chunk sequences of proper nouns
      {<NN>+}                 # chunk consecutive nouns
      """
    cp = nltk.RegexpParser(grammar)  # Define Parser
    SentenceTree = cp.parse(tagged_sent)
    NounPhrases = traverse(SentenceTree)   # collect Noun Phrase
    return(NounPhrases)

sentence = "Michael Jackson likes to eat at McDonalds"
tagged_sent = pos_tag(sentence.split())  
NP = nounPhrase(tagged_sent)  
print(NP)

目前打印:
(NP Michael / NNP Jackson / NNP)
(NP麦当劳/ NNP)
并将’无’存储到NP

解决方法

def extract_np(psent):
  for subtree in psent.subtrees():
    if subtree.label() == 'NP':
      yield ' '.join(word for word,tag in subtree.leaves())


cp = nltk.RegexpParser(grammar)
parsed_sent = cp.parse(tagged_sent)
for npstr in extract_np(parsed_sent):
    print (npstr)
原文链接:https://www.f2er.com/python/185843.html

猜你在找的Python相关文章