Choose RAG Chunking by Document Type and Answer Shape

A chunking strategy should preserve the information needed to answer the questions your documents attract. A definition, a contract condition, a table lookup, and a code explanation do not necessarily benefit from the same boundaries.

Use a document-and-question matrix before choosing one global chunk size. The aim is to keep supporting evidence intact within a manageable retrieval budget.

Pair each document type with a representative question

Material	Example question	Boundary risk
Policy	When does the exception apply?	Rule separated from exception
Procedure	What must happen before step three?	Prerequisite omitted
Table	Which rate applies to this tier?	Value separated from row and column labels
Code	What calls this helper?	Function separated from relevant usage
Meeting notes	Was this proposal accepted?	Discussion confused with decision

Label the supporting span before comparing splitters. Otherwise, it is easy to reward a chunk for matching the topic while overlooking the missing condition.

Hold retrieval conditions steady

Keep the corpus version, model, filters, ranking settings, and answer prompt fixed while testing boundaries. Compare both a fixed result count and a fixed context-token budget. Report duplicate evidence separately from useful coverage.

If a structural splitter already preserves the needed evidence, a more complex method may add cost without benefit. The semantic-chunking guide explains how to test semantic boundaries as a separate intervention.

Make revisions part of the experiment

Edit a paragraph near a boundary and inspect which chunk IDs change. A splitter that shifts every later boundary can increase reprocessing and complicate citation stability. Preserve source revision information regardless of the method.

Delete a section and verify that its old chunks no longer supply current answers. Chunk quality includes maintaining the representation as sources change, not just initial retrieval performance.

Choose a default and explicit exceptions

A product can use a simple default for ordinary prose and separate treatment for tables or code. Record why each exception exists and keep a representative failure fixture. Avoid accumulating special cases without measured benefit.

The main chunking guide connects these choices to the full pipeline. To compare a managed path, try Supermemory with the same document matrix and inspect the actual evidence returned for each question type.