Same Knowledge, Different Graph: Knowledge-Graph Foundation Models Are Not Schema-Invariant

Knowledge-graph foundation models (KGFMs) are designed to be equivariant to the renaming of entities and relations, a property that supports transfer to unseen vocabularies. We ask whether they are also invariant to how the same knowledge is written down, for instance, as a direct edge, a reified event node, or a Freebase-style mediator. These encodings are not isomorphic, yet each can be made answer-preserving for a declared family of queries. We formalize such schema rewrites and evaluate KGFMs with a context-only protocol in which the background relations outside a fold are rewritten while the held-out queries and their candidates stay fixed. Under reification of the evidence, ULTRA’s mean reciprocal rank falls by 17–55% relative to the original view on six of seven benchmark graphs and its top-1 answer changes on 60–90% of queries; on CoDExSmall, DBpedia100k and WN18RR, where deleting the rewritten facts measurably hurts, re-encoding them costs 0.8–1.3 times as much as deleting them, and a Freebase-style expansion of the collapsed mediator relations of FB15k-237 costs 17%. Two further message-passing models behave similarly. We relate the failure to a receptive-field idealization of the entity encoder and to a removable query-conditioning asymmetry in ULTRA. Among remedies, a learned consistency objective does not consistently improve over augmentation. A structural normalizer with a relation-purity test, when the motifs in use are recognized, recovers near-original MRR and high top-1 agreement on every rewrite we constructed, with residual discrepancies where motifs have low support. It leaves the eight untouched graphs we tested unchanged; incomplete motif recognition remains its main open failure.