RippleKB: Finding What an Edit Changes Across Linked Documents

Editing one fact can change a derived quantity, comparison, or other statement across linked documents. RippleKB evaluates whether systems can recover a constructed set of affected source units completely. Each item edits one source fact in a small set of linked documents. The proposed answer key is a hidden dependency closure, with unaffected units also present. A system returns a ranked list of source units, word for word, under a review rule tied to the constructed affected-set size. We regenerate every item from a public multi-hop corpus and test identifier-order, document-position, lexical, and supporting-fact rankings, alongside role and template concentration checks. We release the audit protocol under which the proposed closure is to be reviewed unit by unit. We report how far retrieval-style and language-model baselines get toward recovering the constructed closure completely on the machine-validated candidate set; human validation was not obtained. Complete recovery tests whether a ranking includes the entire constructed target, while exact-copy measures separately assess preservation of source text.