Files
searchi/fixtures/relevance/README.md
T
karl caf6a2f82e
Core CI / core (ubuntu-latest) (push) Failing after 3m27s
Core CI / core (macos-latest) (push) Canceled after 0s
Core CI / core (windows-latest) (push) Canceled after 0s
Core CI / desktop (ubuntu-latest) (push) Successful in 5m45s
Core CI / desktop (macos-latest) (push) Canceled after 0s
Core CI / desktop (windows-latest) (push) Canceled after 0s
feat: integrate Google semantic search and branded desktop launcher
2026-10-12 17:44:56 +02:00

15 lines
838 B
Markdown

# Retrieval regression corpus
This synthetic seed corpus contains 20 documents and 24 predetermined queries:
exact filenames, error/invoice identifiers, remembered concepts and English/German
cross-language retrieval. Each query labels one expected file. Supplier-contract
termination and meeting cancellation deliberately share words but differ in intent.
Report top-1 accuracy, recall@10, per-query rank and latency. Keep failures in
reports; do not rewrite expected answers or remove difficult queries to make a
model pass. Evaluate lexical, semantic and hybrid modes on the same corpus.
This corpus is a regression fixture, not a representative user dataset. Production
quality needs a larger independently labelled corpus, varied document lengths,
PDF/OCR/media cases, ambiguous/no-answer queries and measured filter correctness.