corpus-retrieval-lab
Benchmark current research-query and direct lexical baselines against experimental vector, BM25, typed concept-graph PPR, and RRF source selection without replacing production retrieval.
- License 许可
- MIT
- 所属仓库
- jmagly/aiwg
- 最近更新
- 2026-11-12
- Stars
- ★ 229
- Forks
- 36
01 前言 Front Matter
- name
- corpus-retrieval-lab
- triggers
- [ "benchmark corpus retrieval", "hybrid retrieval lab", "compare research query retrieval" ]
- namespace
- aiwg
- platforms
- [ "all" ]
- commandHint
- { "category": "research-retrieval", "allowedTools": "Read, Bash", "argumentHint": "--queries <jsonl> --concepts <json> [--expected-scheme-hash <sha256>] [--json] [--out <path>]" }
- description
- Benchmark current research-query and direct lexical baselines against experimental vector, BM25, typed concept-graph PPR, and RRF source selection without replacing production retrieval.
03 SKILL.md 正文
Corpus Retrieval Lab
Run the local experimental benchmark:
aiwg corpus retrieval-lab --queries <jsonl> --concepts <json> --json
Use reviewed narrow implementation questions with expected REF evidence. Preserve the current research-query behavior regardless of the result; the report may only recommend a later explicit adoption decision.
The lab reports baseline and hybrid Hit@k, MRR, latency, failures, confidence/dispersion, faithfulness, and concept-scheme drift. Use --expected-scheme-hash when comparing runs across time.
See docs/guides/corpus-retrieval-lab.md for fixture schemas and interpretation.
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