用 spacy 找到 noun_chunk 的根的 POS

Question

使用 spacy 时，您可以轻松地循环遍历文本的 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']

还可以得到名词块的"root"：

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

如何获得每个单词的词性（即使看起来 noun_phrase 的词根始终是名词），以及如何获得引理、形状和单词该特定单词的单数。

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 "processing" 是一个名词，所以它的引理是 "processing"，而不是 "process" 这是动词 "processing" 的引理.

用 spacy 找到 noun_chunk 的根的 POS

finding the POS of the root of a noun_chunk with spacy

nlp

root

spacy

chunks

lemmatization