Unverified50% confidenceFactExact time
Retrieval systems match based on semantic similarity and cannot determine whether returned documents are truly correct, only whether they are relevant.
1
Sources
50%
Confidence
Long-term
Relevance
9/30/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedVector search can retrieve text chunks with high similarity scores, but cannot explain the reasoning logic behind answers, nor structurally connect facts scattered across different documents.78% similarUnverifiedRelying solely on vector similarity retrieval often yields imprecise recall, necessitating a hybrid retrieval approach that combines keyword-based retrieval.77% similarUnverifiedRAG检索依赖语义向量相似度匹配，无法检索只存在于PR评论或工程师记忆里的隐性决策知识69% similarUnverifiedIntroducing fuzzy semantic matching at the caching layer is essentially trading accuracy for performance, and may return incorrect answers that the user did not request.68% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/961121API
curl https://kongchang.com/api/v1/knowledge/claims/961121MCP
get_claim(id=961121)