{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,13]],"date-time":"2026-02-13T15:55:00Z","timestamp":1770998100146,"version":"3.50.1"},"reference-count":10,"publisher":"Association for Computing Machinery (ACM)","issue":"12","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Proc. VLDB Endow."],"published-print":{"date-parts":[[2017,8]]},"abstract":"\n The management of uncertainty is crucial when harvesting structured content from unstructured and noisy sources. Knowledge Graphs (\n kg<\/jats:sc>\n s), maintaining both numerical and non-numerical facts supported by an underlying schema, are a prominent example. Knowledge Graph management is challenging because: (i) most of existing\n kg<\/jats:sc>\n s focus on static data, thus impeding the availability of timewise knowledge; (ii) facts in\n kg<\/jats:sc>\n s are usually accompanied by a confidence score, which witnesses how likely it is for them to hold.\n <\/jats:p>\n \n We demonstrate T\n e<\/jats:sc>\n C\n o<\/jats:sc>\n R\n e<\/jats:sc>\n , a system for temporal inference and conflict resolution in uncertain temporal knowledge graphs (\n utkg<\/jats:sc>\n s). At the heart of T\n e<\/jats:sc>\n C\n o<\/jats:sc>\n R\n e<\/jats:sc>\n are two state-of-the-art probabilistic reasoners that are able to deal with temporal constraints efficiently. While one is scalable, the other can cope with more expressive constraints. The demonstration will focus on enabling users and applications to find inconsistencies in\n utkg<\/jats:sc>\n s. T\n e<\/jats:sc>\n C\n o<\/jats:sc>\n R\n e<\/jats:sc>\n provides an interface allowing to select\n utkg<\/jats:sc>\n s and editing constraints; shows the maximal consistent subset of the\n utkg<\/jats:sc>\n , and displays statistics (e.g., number of noisy facts removed) about the debugging process.\n <\/jats:p>","DOI":"10.14778\/3137765.3137811","type":"journal-article","created":{"date-parts":[[2017,9,7]],"date-time":"2017-09-07T13:35:53Z","timestamp":1504791353000},"page":"1929-1932","source":"Crossref","is-referenced-by-count":7,"title":["T\n e<\/scp>\n C\n o<\/scp>\n R\n e<\/scp>"],"prefix":"10.14778","volume":"10","author":[{"given":"Melisachew W.","family":"Chekol","sequence":"first","affiliation":[{"name":"University of Mannheim"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Giuseppe","family":"Pirr\u00f2","sequence":"additional","affiliation":[{"name":"ICAR-CNR, Rende(CS), Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Joerg","family":"Schoenfisch","sequence":"additional","affiliation":[{"name":"University of Mannheim"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Heiner","family":"Stuckenschmidt","sequence":"additional","affiliation":[{"name":"University of Mannheim"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2017,8]]},"reference":[{"key":"e_1_2_1_1_1","volume-title":"Hinge-loss markov random fields and probabilistic soft logic. CoRR, abs\/1505.04406","author":"Bach S. H.","year":"2015","unstructured":"S. H. Bach , M. Broecheler , B. Huang , and L. Getoor . Hinge-loss markov random fields and probabilistic soft logic. CoRR, abs\/1505.04406 , 2015 . S. H. Bach, M. Broecheler, B. Huang, and L. Getoor. Hinge-loss markov random fields and probabilistic soft logic. CoRR, abs\/1505.04406, 2015."},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/1897816.1897839"},{"key":"e_1_2_1_3_1","first-page":"1017","volume-title":"Proc. of ECAI 2016","author":"Chekol M. W.","year":"2016","unstructured":"M. W. Chekol , J. Huber , C. Meilicke , and H. Stuckenschmidt . Markov logic networks with numerical constraints . In Proc. of ECAI 2016 , pages 1017 -- 1025 , 2016 . M. W. Chekol, J. Huber, C. Meilicke, and H. Stuckenschmidt. Markov logic networks with numerical constraints. In Proc. of ECAI 2016, pages 1017--1025, 2016."},{"key":"e_1_2_1_4_1","volume-title":"Proc. of AAAI 2017","author":"Chekol M. W.","year":"2017","unstructured":"M. W. Chekol , G. Pirr\u00f2 , J. Schoenfisch , and H. Stuckenschmidt . Marrying Uncertainty and Time in Knowledge Graphs . In Proc. of AAAI 2017 , 2017 . M. W. Chekol, G. Pirr\u00f2, J. Schoenfisch, and H. Stuckenschmidt. Marrying Uncertainty and Time in Knowledge Graphs. In Proc. of AAAI 2017, 2017."},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.14778\/2556549.2556564"},{"key":"e_1_2_1_6_1","first-page":"1385","volume-title":"AAAI","author":"Ling X.","year":"2010","unstructured":"X. Ling and D. S. Weld . Temporal Information Extraction . In AAAI , pages 1385 -- 1390 , 2010 . X. Ling and D. S. Weld. Temporal Information Extraction. In AAAI, pages 1385--1390, 2010."},{"key":"e_1_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE.2016.7498350"},{"key":"e_1_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-006-5833-1"},{"key":"e_1_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10817-007-9076-z"},{"key":"e_1_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.14778\/3007263.3007284"}],"container-title":["Proceedings of the VLDB Endowment"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.14778\/3137765.3137811","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,28]],"date-time":"2022-12-28T10:05:47Z","timestamp":1672221947000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.14778\/3137765.3137811"}},"subtitle":["temporal conflict resolution in knowledge graphs"],"short-title":[],"issued":{"date-parts":[[2017,8]]},"references-count":10,"journal-issue":{"issue":"12","published-print":{"date-parts":[[2017,8]]}},"alternative-id":["10.14778\/3137765.3137811"],"URL":"https:\/\/doi.org\/10.14778\/3137765.3137811","relation":{},"ISSN":["2150-8097"],"issn-type":[{"value":"2150-8097","type":"print"}],"subject":[],"published":{"date-parts":[[2017,8]]}}}