一尘不染

NLTK-块语法不读逗号

python

from nltk.chunk.util import tagstr2tree
from nltk import word_tokenize, pos_tag
text = "John Rose Center is very beautiful place and i want to go there with Barbara Palvin. Also there are stores like Adidas ,Nike ,Reebok Center."
tagged_text = pos_tag(text.split())

grammar = "NP:{<NNP>+}"

cp = nltk.RegexpParser(grammar)
result = cp.parse(tagged_text)

print(result)

输出:

(S
  (NP John/NNP Rose/NNP Center/NNP)
  is/VBZ
  very/RB
  beautiful/JJ
  place/NN
  and/CC
  i/NN
  want/VBP
  to/TO
  go/VB
  there/RB
  with/IN
  (NP Barbara/NNP Palvin./NNP)
  Also/RB
  there/EX
  are/VBP
  stores/NNS
  like/IN
  (NP Adidas/NNP ,Nike/NNP ,Reebok/NNP Center./NNP))

我用于分块的语法仅适用于nnp标记,但是如果单词与逗号连续,它们仍将在同一行上。

(S
  (NP John/NNP Rose/NNP Center/NNP)
  is/VBZ
  very/RB
  beautiful/JJ
  place/NN
  and/CC
  i/NN
  want/VBP
  to/TO
  go/VB
  there/RB
  with/IN
  (NP Barbara/NNP Palvin./NNP)
  Also/RB
  there/EX
  are/VBP
  stores/NNS
  like/IN
  (NP Adidas,/NNP)
  (NP Nike,/NNP)
  (NP Reebok/NNP Center./NNP))

我应该在“ grammar =“中写什么,还是可以像上面写的那样编辑输出?如您所见,我只为我的命名实体项目解析专有名词,请帮助我。


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2021-01-20

共1个答案

一尘不染

使用word_tokenize(string)代替string.split()

>>> import nltk
>>> from nltk.chunk.util import tagstr2tree
>>> from nltk import word_tokenize, pos_tag
>>> text = "John Rose Center is very beautiful place and i want to go there with Barbara Palvin. Also there are stores like Adidas ,Nike ,Reebok Center."
>>> tagged_text = pos_tag(word_tokenize(text))
>>> 
>>> grammar = "NP:{<NNP>+}"
>>> 
>>> cp = nltk.RegexpParser(grammar)
>>> result = cp.parse(tagged_text)
>>> 
>>> print(result)
(S
  (NP John/NNP Rose/NNP Center/NNP)
  is/VBZ
  very/RB
  beautiful/JJ
  place/NN
  and/CC
  i/NN
  want/VBP
  to/TO
  go/VB
  there/RB
  with/IN
  (NP Barbara/NNP Palvin/NNP)
  ./.
  Also/RB
  there/EX
  are/VBP
  stores/NNS
  like/IN
  (NP Adidas/NNP)
  ,/,
  (NP Nike/NNP)
  ,/,
  (NP Reebok/NNP Center/NNP)
  ./.)
2021-01-20