Grounding
Last updated: July 26, 2026
Grounding means tying a claim to real, independent evidence that actually backs it. A grounded claim is one you can trace to a source that says the same thing. It is the core operation of verification: without grounding, a claim is just fluent text that might or might not be true.
What is grounding?
Grounding is the act of connecting a claim to independent evidence that actually supports it. A grounded claim is one you can trace to a source that says the same thing; an ungrounded claim is fluent text with nothing under it.
The word is used two ways. In model design, 'grounding' means feeding a model real documents so its answer is anchored to them (see RAG). In verification, grounding means the reverse audit: taking a finished claim and testing whether an independent source confirms it. This page is about the second.
The key word is independent. Grounding a claim against the same model that produced it, or against a source the model was told to cite, proves nothing. Real grounding uses sources the model did not control.
Why grounding is the core of verification
Everything else in a verifier exists to make grounding possible and honest. You extract claims so each can be grounded on its own; you assign verdicts based on what grounding finds; you return unverifiable when grounding turns up nothing authoritative.
Grounding is also what separates real verification from two things that look like it but are not. A citation existing is not grounding — the cited source has to actually say what the claim says (see citations vs claims). And several models agreeing is not grounding — shared belief is not evidence.
Mephistopheles grounds each claim against multiple independent channels — semantic retrieval over a corpus, live web search, structured knowledge like Wikidata and Wikipedia, and tools — then judges the result. See how it works.
A worked example
An AI answer claims: "The James Webb Space Telescope launched in December 2021." To ground it, a verifier searches independent sources — space-agency records, reference databases — and finds agreement on the launch date. Verdict: supported.
Now a subtler claim: "Study X found a 40% improvement." The paper exists, so a naive checker might pass it. Grounding goes further: it reads the source and finds the paper reported 14%, not 40%. The citation was real but did not back the sentence. Verdict: contradicted. That gap is the whole reason grounding must read sources, not just confirm they exist.
Frequently asked questions
What does it mean to ground a claim?
To ground a claim is to find an independent, authoritative source that confirms or refutes it, and to check that the source actually says what the claim says. A grounded claim is traceable to evidence; an ungrounded one is just plausible-sounding text. See source-grounding.
Is grounding the same as citing a source?
No. A citation names a source; grounding verifies that the named source supports the specific claim. A model can cite a real paper that says nothing about its sentence. Grounding reads the source to confirm the match. See citations vs claims.
Why do the sources have to be independent?
Because grounding a claim against the model that made it, or against a source the model chose, just echoes the model's belief. Independent sources — ones the model did not control — are the only ones that can actually test the claim rather than confirm it circularly.
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