Chunking

Splitting a document into smaller passages so each can be embedded, indexed and retrieved independently in a RAG pipeline.

How you chunk determines what an agent retrieves; clean headings and self-contained sections (the same structure that makes content answer-first) chunk cleanly and lower Cost of Retrieval.

term
Chunking
category
knowledge-memory
short_def
Splitting a document into smaller passages so each can be embedded, indexed and retrieved independently in a RAG pipeline.
long_def
Chunking decides the unit of retrieval: documents are cut into passages (by size, by heading, or semantically) before embedding, so a query returns the few most relevant chunks rather than a whole document. Chunk size is a tradeoff — too large dilutes relevance, too small loses context.
see_also
rag embeddings reranking
etymology_origin
— verify-against-primary-at-build ↗ https://en.wikipedia.org/wiki/Retrieval-augmented_generation — 'chunking' is standard RAG-pipeline terminology
related_to
rag embeddings reranking vector-database
contrast_with
Unlike indexing a whole document as one unit, chunking retrieves passage-level pieces, so an agent gets the relevant paragraph instead of the entire file.
example
A 40-page manual chunked by section lets a query return just the two paragraphs that answer it, keeping the agent's context window focused.
source
https://en.wikipedia.org/wiki/Retrieval-augmented_generation
status
active
why_it_matters
How you chunk determines what an agent retrieves; clean headings and self-contained sections (the same structure that makes content answer-first) chunk cleanly and lower Cost of Retrieval.
sameAs
https://en.wikipedia.org/wiki/Retrieval-augmented_generation
bridge_entity
rag
last_verified
2026-07-06
md_twin
/glossary/chunking.md

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