Chunking

Chunking is a natural language processing technique used to extract meaningful phrases or chunks from sentences. It involves grouping together words or parts of sentences based on certain patterns or grammatical structures.

How does Chunking work?

1. Tokenization: The sentence is first divided into individual words or tokens.

2. Part-of-speech tagging: Each word is assigned a specific grammatical category such as noun, verb, adjective, etc.

3. Chunk parsing: Using predefined syntactic patterns or rules, the words are grouped together to form meaningful phrases or chunks.

Examples of Chunking

Let’s consider the sentence: “The black cat chased the mouse.”

Using chunking, we can extract the following chunks:

• Chunk 1: “The black cat” (noun phrase)
• Chunk 2: “chased” (verb phrase)
• Chunk 3: “the mouse” (noun phrase)

The extracted chunks provide a more meaningful representation of the sentence, which can be further utilized in various natural language processing tasks.