Semantic Chunking

Semantic Chunking splits text along meaning boundaries rather than fixed lengths like 'every 500 tokens'. Each chunk closes around a coherent unit — one topic, one definition, one step — which preserves context when an LLM lifts the passage into an answer.

On the content side, the leverage is structural: the page has to be written so that meaning-aware splitting is even possible. An H2 section that quietly mixes several topics, or a paragraph that wraps up two conclusions at once, makes clean semantic chunks hard and pulls citation odds down.

Practical move — apply 'one section, one answerable question' a little more strictly. Lead the section with the answer sentence, follow with evidence and examples, and close the section before pivoting topics. Meaning-aligned chunks fall out of that structure almost for free.