Review Search / Retrieval

Search is the process of looking through available information to find the most relevant items, documents, or answers.

Search or retrieval is the process of finding items that are relevant to a query or information need. A system may use keywords, structured filters, learned representations, ranking, or several methods together.

Retrieved material often becomes evidence or model context. Quality depends on indexing, query design, ranking, permissions, freshness, and whether the result actually supports the claim being made.

A support assistant searches approved manuals for passages about a specific error code and passes the highest-ranked relevant passages to the response step.

Retrieval does not prove that a result is true or sufficient. It finds candidates; verification and interpretation remain separate work.

Search finds candidates; verification decides what they support.

* [[retrieval-augmented-generation|Retrieval-Augmented Generation]] * [[grounding|Grounding]] * [[embedding|Embedding]] * [[verification|Verification]]

* [Christopher Manning, Prabhakar Raghavan, and Hinrich Schütze, “Introduction to Information Retrieval”](https://nlp.stanford.edu/IR-book/) — provides the established information-retrieval foundation for indexing, querying, and ranking relevant documents. * [Patrick Lewis and colleagues, “Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks”](https://arxiv.org/abs/2005.11401) — shows retrieved passages used as external context for generation.

* Compare [[retrieval-augmented-generation|Retrieval-Augmented Generation]], [[grounding|Grounding]], [[embedding|Embedding]], and [[verification|Verification]] to place Search / Retrieval in the surrounding system. * Follow the cited source material above for the method, standard, or research context behind this draft.