GraphRAGProv：GraphRAG 结合 how-provenance 溯源
GraphRAGProv: GraphRAG Meets How-Provenance
AI 导读
GraphRAGProv 提出在源文本锚定的 RDF 图上执行 SPARQL 查询，在生成答案的同时计算 how-provenance 多项式，记录使用了哪些语句及其组合方式，用户可循链接核查语句是否忠实于原文。交互式演示覆盖两个多跳 QA benchmark 的 400 个案例，即使最终答案正确也能暴露抽取与查询错误。
正文 · 原文
Abstract:GraphRAG systems often use knowledge graphs to retrieve relevant context for an LLM that produces the final answer. That makes answers more inscrutable and therefore less appealing for domains where transparency is paramount. We present GraphRAGProv, an architecture that executes SPARQL queries over source-grounded RDF graphs to compute answers and their how-provenance polynomials. These polynomials record which statement occurrences were used and how they were combined. Because each occurrence is linked to its source text, users can follow these links to check whether the extracted statements reflect the text and whether the query combines them to answer the question. Querying thereby becomes a way to inspect and evaluate the text-to-graph transformation. Our interactive demo examines 400 cases from two multi-hop QA benchmarks, revealing extraction and query errors even when the final answer is correct.
| Subjects: | Artificial Intelligence (cs.AI); Databases (cs.DB) |
| ACM classes: | I.2; H.2 |
| Cite as: | arXiv:2610.37237 [cs.AI] |
| (or arXiv:2610.37237v1 [cs.AI] for this version) | |
| https://doi.org/10.48550/arXiv.2610.37237 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: Luis Galárraga [view email]
[v1]
Tue, 27 Oct 2026 13:42:48 UTC (10,869 KB)
来源：arXiv cs.AI · arxiv.org