How to extract special characters using NLTK RegexpParser Chunk for POS_tagged words in Python

Question

I have some text for example say: 80% of $300,000 Each Human Resource/IT Department.

I would need to extract $300,000 along with the words Each Human Resource/IT Department

I have used pos tagging to tag the words after tokenizing. I was able to extract 300,000 but not able to extract $ sign along with it.

What I have so far:

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)

chunked output when coverted to list - ['80 %', '300,000', 'Each Human Resource/IT Department']

What I wanted : ['80 %', '**$**300,000', 'Each Human Resource/IT Department']

I tried

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

It still doesn't work. So, all I need is a $ along with CD

Answer 1

You need to add <\$>? in your grammar.

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

Code :

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)

Output :

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