用 spacy 找到名词块的根的 POS

Question

使用 spacy 时，您可以轻松地遍历文本的 noun_phrases，如下所示：

S='This is an example sentence that should include several parts and also make clear that studying Natural language Processing is not difficult'
nlp = spacy.load('en_core_web_sm')
doc = nlp(S)

[chunk.text for chunk in doc.noun_chunks]
# = ['an example sentence', 'several parts', 'Natural language Processing']

你也可以得到名词块的“根”：

[chunk.root.text for chunk in doc.noun_chunks]
# = ['sentence', 'parts', 'Processing']

如何获得每个单词的词性（即使名词短语的词根始终是名词），以及如何获得该特定单词的引理、形状和单数单词。

这可能吗？

谢谢。

Answer 1

每个chunk.root 都是一个Token，您可以在其中获得不同的属性，包括lemma_ 和pos_（或者tag_，如果您更喜欢PennTreekbak POS 标签）。

import spacy
S='This is an example sentence that should include several parts and also make ' \
  'clear that studying Natural language Processing is not difficult'
nlp = spacy.load('en_core_web_sm')
doc = nlp(S)
for chunk in doc.noun_chunks:
    print('%-12s %-6s  %s' % (chunk.root.text, chunk.root.pos_, chunk.root.lemma_))

sentence     NOUN    sentence
parts        NOUN    part
Processing   NOUN    processing

顺便说一句...在这句话中，“处理”是一个名词，所以它的引理是“处理”，而不是“过程”，它是动词“处理”的引理。