Unverified50% confidenceFactExact time
Traditional semantic similarity retrieval based on embedding vectors is a retrospective static semantic matching approach that cannot capture the temporal causal associations between commitments and trigger scenarios.
1
Sources
50%
Confidence
Long-term
Relevance
9/22/2026
First Seen
Sources
Related Entities
Related Claims
VerifiedVector similarity computation typically uses cosine similarity, which measures the angle between vector directions rather than absolute distance and is insensitive to vector magnitude.67% similarUnverified向量检索只能捕捉表面语义相似性，无法理解实体间的结构化关系，对多跳关系问题往往无法给出精确答案66% similarUnverified余弦相似度衡量的是两个向量在高维球面上的角度差异，依赖全局方向信息，忽略嵌入向量各维度之间的局部关系结构64% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/939997API
curl https://kongchang.com/api/v1/knowledge/claims/939997MCP
get_claim(id=939997)