A retrieval chatbot gives wrong answers.
Investigation shows that unrelated documents are retrieved before generation.
What should be evaluated first?
Evaluate whether retrieved documents are relevant, complete, and authorized before evaluating the generated answer.
Detailed explanation
If retrieval supplies poor evidence, generation cannot reliably answer from the source.
UI styling does not measure retrieval quality.
Deletion removes the evidence needed for grounded generation.
Temperature does not fix irrelevant retrieval results.
Check official documentation
Compare the following points with the official documentation.
Amazon Bedrock Knowledge Bases公式の検索・取得結果と引用の説明を確認する。
Official references
What to confirm
取得段階と生成段階を分け、検索結果の関連性を評価する理由を説明できる。
Key points
- Retrieval relevance
- Retrieval stage
- Generation stage
Notes
- Environment: AWS公式AIF-C01試験ガイドとAWS公式ドキュメントの確認
- Compare the definition with the AIF-C01 objective and the service documentation before applying it.
- Keep the concept separate from a particular answer choice or implementation step.
Foundation review
Stage isolation
Poor retrieval can limit answer quality even when the generation model is capable.
Context quality
Retrieved passages should be relevant, current, authorized, and sufficiently complete.