Lesson 19: Why hybrid search and reranking help

One search method recognizes the date, another understands still open. Combining their candidates is the complementary idea behind hybrid retrieval.

First improve candidate coverage

Hybrid retrieval combines methods such as keyword and vector search. Exact signals and paraphrases can complement each other. Fusion, deduplication, and filtering affect results, so test fixed queries.

Raw keyword and vector scores may use different scales, so arbitrary addition is not a universal algorithm. Specified methods such as rank-based fusion combine them. Understand candidate fusion before formulas.

Then decide which candidates should lead

With A/H/D, reranking reconsiders query and candidates to put useful evidence earlier. Gathering quickly and comparing more carefully is a common two-stage approach.

It cannot recover an absent D or invent deposits. More careful comparison can add computation, latency, or cost; measure whether benefits justify them.

Merge candidates for the date question

Simulate keyword D/A/B and semantic A/H/D results. The deduplicated set contains D/A/B/H with necessary A/D. This illustrates a set, not a prescribed final ranking.

For special versus ordinary hours, put A/D before unrelated rules. Their relative order can follow answer needs, but both are required. If initial retrieval lacks D, fix that stage first.

Scores do not decide versions. E/B are similar; high rank does not establish current validity, and historical questions may need E. Preserve dates, status, and scope.

Create another simulation for extending a return date. Fix collection and queries for hybrid comparisons, and fix first-stage candidates for reranking comparisons. Record whether C appears and where it ranks.

Identify the failure first

Missing C leaves nothing for reranking; late C may benefit; leading C followed by a B-based answer needs generation review. Choose a method that fits the cause.

Further reading: Microsoft: Hybrid search overview

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