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Glossary entry chunking

Chunking

How engines split long pages into retrievable pieces. H2 boundaries are the dominant split signal.

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Techniques

Definition

Chunking is the process of splitting a long document into smaller pieces (200-1000 tokens each) so each piece can be independently embedded and retrieved. Most engines chunk at heading boundaries (H1/H2/H3), some chunk by paragraph, some use semantic-similarity-based splits. A page with strong H2 structure yields cleaner chunks; a wall-of-text page chunks awkwardly and underperforms.

Example

A 3000-word page with 6 H2 sections chunks into 6 retrievable pieces, each independently citable. A 3000-word page with no H2s chunks into ~6 arbitrary 500-token pieces that often split mid-thought.

How to optimize

Use H2s every 400-600 words. Make each H2 section self-contained (don't reference earlier sections by 'as discussed above', because engines retrieve sections in isolation). VectorCite's h2-coverage signal scores this.

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