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Chinking In NLP

This article describes chinking in NLP.

Purpose

The chinking is the process of removing specific words (or sequences) from a chunk that was created during chunking.

Consider the following example: -

The quick brown fox jumps over the lazy dog

In the above example, the word jumps is a verb, and the word over is a preposition. So, the words jumps and over should not be a part of a noun phrase. In chinking, we remove these words.

Example

Consider the following example.

import nltk
from nltk import pos_tag, word_tokenize, RegexpParser

sentence = "The quick brown fox jumps over the lazy dog"
tokens = word_tokenize(sentence)
tagged = pos_tag(tokens)

# First, chunk everything
grammar = r"""
  NP: {<.*>+}         # Chunk everything
      }<VB.*|IN>+{    # Chink verbs AND prepositions
"""

chunk_parser = RegexpParser(grammar)
tree = chunk_parser.parse(tagged)

print(tree)

Output

Posted By -	Karan Gupta

Posted On -	Thursday, September 4, 2025

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