Commit Graph
7 Commits
Author SHA1 Message Date
Dylan Couzon 814bdc1a48 clean up messaging 2026-04-20 11:06:41 -04:00
Dylan CouzonandClaude Sonnet 4.6 52a38d255c Link new retrieval quality tutorials from navigation indexes
Updates both search engineering index files (the headless partial and
the tutorials-lp overview) to list Retrieval Quality Fundamentals and
Building a Golden Query Set alongside the existing Retrieval Quality
Evaluation row. The Evaluation row is also retitled from "Measure
quality and tune HNSW parameters" to "Measure ANN recall and tune
HNSW parameters" to match the refactored page.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-20 10:47:02 -04:00
Dylan CouzonandClaude Sonnet 4.6 7d3d44b727 Refactor Retrieval Quality Evaluation to recall terminology
Renames precision to recall throughout the ANN-evaluation tutorial so
the page aligns with the ANN-benchmarks convention and with the new
Retrieval Quality Fundamentals page. The numerical formula is
unchanged: when ANN and exact search both return exactly k items,
recall@k and precision@k are numerically identical.

Other changes:
- Remove the Quality metrics subsection, now covered by the
  Fundamentals page, and replace it with a short link across.
- Bump weight from 4 to 6 so the three retrieval-quality pages
  order as Fundamentals, Golden Query Set, Evaluation.
- Fix a pre-existing prose/code mismatch: the prose said "first
  50000 items" while the code uses range(60000).

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-20 10:46:19 -04:00
Dylan CouzonandClaude Sonnet 4.6 5db9d106aa Add Retrieval Quality Fundamentals and Golden Query Set tutorials
Introduces two new conceptual tutorials under tutorials-search-engineering:

- Retrieval Quality Fundamentals covers the three-level evaluation
  framework (ANN recall, retrieval relevance, business impact), the
  evaluation ladder that connects them in practice, and a which-metric-
  when decision table keyed by scenario and available ground truth.
- Building a Golden Query Set covers query generation at scale (logs,
  LLM synthesis, human annotation) and the failure modes commonly
  lumped together as data leakage: synthetic-query unrealism,
  embedding-model contamination, near-duplicate documents, temporal
  drift, and reviewer reproducibility.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-20 10:42:05 -04:00
Dylan Couzon 12b9380ee2 Update changes.md 2026-04-20 10:31:54 -04:00
Dylan Couzon 0ae51086d6 clean up changes 2026-04-20 10:20:11 -04:00
Dylan Couzon e588e2bf08 add proposed changes 2026-04-16 16:33:07 -04:00