Decoupling Error Attribution in Cloud-Native Graph-RAG: A Data Integrity Diagnostic Framework
Graph-RAG systems often assume pristine data quality, overlooking the severe impact of perturbations in cloud-native databases. This paper proposes a three-layer decoupled diagnostic framework to orthogonally attribute system errors to reasoning loss, Knowledge Graph (KG) defects, and Cypher generation errors. Evaluated on a spatio-temporal ecological KG of the Southeastern Tibet region with eight defect types, results reveal that data integrity, rather than algorithmic reasoning, is the dominant performance bottleneck, with structural defects degrading system accuracy from 0.93 to 0.39. Crucially, we observe a masking-like phenomenon termed the Parametric Knowledge Masking Effect (PKME),...
| Authors | Shuai Yan, Yuhang Wu, Xiaodong Huang et al. |
|---|---|
| Primary category | cs.IR |
| Published | 10 September 2026 |
| Last updated at source | 10 September 2026 |
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