python - 如何使用 NLTK RegexpParser Chunk 为 Python 中的 POS_tagged 词提取特殊字符

Question

例如，我有一些文字说：80% of $300,000 Each Human Resource/IT Department.

我需要$300,000连同单词一起提取Each Human Resource/IT Department

我在标记化后使用 pos 标记来标记单词。我能够提取 300,000 但无法同时提取 $ 符号。

到目前为止我所拥有的：

text = '80% of $300,000 Each Human Resource/IT Department'
train_text = text
sample_text = text
custom_sent_tokenizer = PunktSentenseTokenizer(train_text)
tokenized = custom_sent_tokenizer.tokenize(sample_text)

for i in tokenized:
    words = nltk.word_tokenize(i)
    tagged = nltk.pos_tag(words)

chunkGram = r"""chunk: {<DT>+<NN.*>+<NN.*>?|<NNP>?|<CD>+<NN>?|<NNP>?}"""


chunkParser = nltk.RegexpParser(chunkGram)
chunked = chunkParser.parse(tagged)

转换为列表时的分块输出 -['80 %', '300,000', 'Each Human Resource/IT Department']

我想要什么：['80 %', '**$**300,000', 'Each Human Resource/IT Department']

我试过

chunkGram = r"""chunk: {**</$CD>|**<DT>+<NN.*>+<NN.*>?|<NNP>?|<CD>+<NN>?|?}"""

它仍然不起作用。所以，我只需要一张$和CD

Answer 1

您需要添加 <\$>? 在你的语法中。

chunkGram = r"""chunk: {<DT>+<NN.*>+<NN.*>?|<\$>?<CD>+<NN>?|<NNP>?}"""

代码 ：

import nltk
from nltk.tokenize import PunktSentenceTokenizer

text = '80% of $300,000 Each Human Resource/IT Department'
train_text = text
sample_text = text
custom_sent_tokenizer = PunktSentenceTokenizer(train_text)
tokenized = custom_sent_tokenizer.tokenize(sample_text)

for i in tokenized:
    words = nltk.word_tokenize(i)
    tagged = nltk.pos_tag(words)

chunkGram = r"""chunk: {<DT>+<NN.*>+<NN.*>?|<\$>?<CD>+<NN>?|<NNP>?}"""

chunkParser = nltk.RegexpParser(chunkGram)
chunked = chunkParser.parse(tagged)

print(chunked)

输出 ：

(S
  (chunk 80/CD %/NN)
  of/IN
  (chunk $/$ 300,000/CD)
  (chunk Each/DT Human/NNP Resource/IT/NNP Department/NNP))