{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,12]],"date-time":"2026-10-12T23:05:48Z","timestamp":1791846348834,"version":"4.3.4"},"publisher-location":"California","reference-count":0,"publisher":"International Joint Conferences on Artificial Intelligence Organization","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,9]]},"abstract":"<jats:p>We propose a new framework for combining entity resolution and query answering in knowledge bases (KBs) with tuple-generating dependencies (tgds) and equality-generating dependencies (egds) as rules. We define the semantics of the KB in terms of special instances that involve equivalence classes of entities and sets of values. Intuitively, the former collect all entities denoting the same real-world object, while the latter collect all alternative values for an attribute. This approach allows us to both resolve entities and bypass possible inconsistencies in the data. We then design a chase procedure that is tailored to this new framework and has the feature that it never fails; moreover, when the chase procedure terminates, it produces a universal solution, which in turn can be used to obtain the certain answers to conjunctive queries. We finally discuss challenges arising when the chase does not terminate.<\/jats:p>","DOI":"10.24963\/kr.2023\/23","type":"proceedings-article","created":{"date-parts":[[2023,7,31]],"date-time":"2023-07-31T22:27:47Z","timestamp":1690842467000},"page":"229-239","source":"Crossref","is-referenced-by-count":5,"title":["A Framework for Combining Entity Resolution and Query Answering in Knowledge Bases"],"prefix":"10.24963","author":[{"given":"Ronald","family":"Fagin","sequence":"first","affiliation":[{"name":"IBM Almaden Research Center"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Phokion G.","family":"Kolaitis","sequence":"additional","affiliation":[{"name":"University of California Santa Cruz"},{"name":"IBM Research"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Domenico","family":"Lembo","sequence":"additional","affiliation":[{"name":"Sapienza University of Rome"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lucian","family":"Popa","sequence":"additional","affiliation":[{"name":"IBM Almaden Research Center"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Federico","family":"Scafoglieri","sequence":"additional","affiliation":[{"name":"Sapienza University of Rome"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"10584","event":{"name":"20th International Conference on Principles of Knowledge Representation and Reasoning {KR-2023}","theme":"Artificial Intelligence","location":"Rhodes, Greece","acronym":"KR-2023","number":"20","sponsor":["Artificial Intelligence Journal","Principles of Knowledge Representation and Reasoning Inc.","Academic College of Tel-Aviv","European Association for Artificial Intelligence","National Science Foundation"],"start":{"date-parts":[[2023,9,2]]},"end":{"date-parts":[[2023,9,8]]}},"container-title":["Proceedings of the Twentieth International Conference on Principles of Knowledge Representation and Reasoning"],"original-title":[],"deposited":{"date-parts":[[2023,7,31]],"date-time":"2023-07-31T22:28:10Z","timestamp":1690842490000},"score":1,"resource":{"primary":{"URL":"https:\/\/proceedings.kr.org\/2023\/23"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2023,9]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/kr.2023\/23","relation":{},"subject":[],"published":{"date-parts":[[2023,9]]}}}