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retrieval-quality-fundamentals: structure & scope pass

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- Add "why measure retrieval quality" lead-in paragraph
- Expand ANN on first use; flag sparse vectors as out of scope
  for layer 1 (they use exact matching)
- Add LLM-as-judge to layer-2 ground-truth options
- Break the Tooling bullet into per-layer recommendations: Web UI
  for L1, ranx for L2, Ragas/Phoenix/DeepEval for L3
- Reorder Quality Metrics so layer 1 (ANN recall formula + exact
  kNN equivalence) comes before the generic layer-2 relevance
  metrics; trim a redundant sentence
- Add end-to-end answer quality as a distinct third layer in the
  prose intro so it matches the ladder table's four rows
- Standardize vocabulary on "layer" (was mixing "level" in the
  intro with "layer" everywhere else); update the section anchor
  to #connecting-the-layers-in-practice in this file and the two
  cross-linking tutorials

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
This commit is contained in:
Dylan Couzon
2026-04-22 22:31:35 -04:00
co-authored by Claude Opus 4.7
parent 5748d6db8c
commit e2df842fb5
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qdrant-landing/content/documentation/tutorials-search-engineering/retrieval-quality-golden-set.md
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| Time: 40 min | Level: Intermediate | | |
|--------------|---------------------|--|----|
This tutorial covers **layer 2** of the <a href="/documentation/tutorials-search-engineering/retrieval-quality-fundamentals/#connecting-the-levels-in-practice" target="_blank">evaluation ladder</a>: **retrieval relevance**. Measuring how well retrieved results match real user intent requires a labeled dataset of queries paired with their expected relevant documents (commonly called a *golden query set* or *ground truth*). For layer 1 (ANN precision against exact kNN), which needs no relevance labels, use the **Search Quality** tab in the <a href="/documentation/web-ui/" target="_blank">Qdrant Web UI</a>.
This tutorial covers **layer 2** of the <a href="/documentation/tutorials-search-engineering/retrieval-quality-fundamentals/#connecting-the-layers-in-practice" target="_blank">evaluation ladder</a>: **retrieval relevance**. Measuring how well retrieved results match real user intent requires a labeled dataset of queries paired with their expected relevant documents (commonly called a *golden query set* or *ground truth*). For layer 1 (ANN precision against exact kNN), which needs no relevance labels, use the **Search Quality** tab in the <a href="/documentation/web-ui/" target="_blank">Qdrant Web UI</a>.
## Generating Queries