# Citation extraction

**Source:** https://promtable.com/glossary/citation-extraction

> Citation extraction is the technique of attaching source URLs to LLM-generated claims — critical for AI search products to be trustworthy and to give users a way to verify generated content.

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Citation extraction is the technique of attaching source URLs to LLM-generated claims — critical for AI search products to be trustworthy and to give users a way to verify generated content.

Generative AI without citations is a black box; users can't verify, can't follow up, can't trust. Citation extraction makes the model emit source URLs alongside generated text, either inline (`The capital is Paris [^1]`) or as a structured `citations` field. Implementations: (1) constrained decoding to force citation tokens, (2) post-hoc retrieval matching generated claims to retrieved chunks (BM25 / vector / NLI), (3) tool-use protocols where the search tool returns sources the model must reference. Production leaders: Perplexity, ChatGPT Search, Claude with web search, Gemini AI Overview — all attach citations. Quality matters: a citation that doesn't support the claim is worse than no citation. [[grounding]] is the broader practice this fits into.

## When to use

- AI search products.
- Anything where the user needs to verify claims.

## Common mistakes

- Attaching the search tool's first result regardless of relevance — citations don't support claims.
- Skipping citation in B2C 'just give the answer' products — trust collapses on first hallucination.

## Related terms

- [grounding](https://promtable.com/glossary/grounding)
- [ai-search-engine](https://promtable.com/glossary/ai-search-engine)
- [web-retrieval-tool](https://promtable.com/glossary/web-retrieval-tool)

*Last updated: 2026-06-01*
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Original page: https://promtable.com/glossary/citation-extraction
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