{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,16]],"date-time":"2025-10-16T06:57:28Z","timestamp":1760597848953},"reference-count":5,"publisher":"MIT Press - Journals","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["TACL"],"published-print":{"date-parts":[[2018,12]]},"abstract":"<jats:p>Given a knowledge base or KB containing (noisy) facts about common nouns or generics, such as \u201call trees produce oxygen\u201d or \u201csome animals live in forests\u201d, we consider the problem of inferring additional such facts at a precision similar to that of the starting KB. Such KBs capture general knowledge about the world, and are crucial for various applications such as question answering. Different from commonly studied named entity KBs such as Freebase, generics KBs involve quantification, have more complex underlying regularities, tend to be more incomplete, and violate the commonly used locally closed world assumption (LCWA). We show that existing KB completion methods struggle with this new task, and present the first approach that is successful. Our results demonstrate that external information, such as relation schemas and entity taxonomies, if used appropriately, can be a surprisingly powerful tool in this setting. First, our simple yet effective knowledge guided tensor factorization approach achieves state-of-the-art results on two generics KBs (80% precise) for science, doubling their size at 74%\u201386% precision. Second, our novel taxonomy guided, submodular, active learning method for collecting annotations about rare entities (e.g., oriole, a bird) is 6x more effective at inferring further new facts about them than multiple active learning baselines.<\/jats:p>","DOI":"10.1162\/tacl_a_00015","type":"journal-article","created":{"date-parts":[[2018,12,10]],"date-time":"2018-12-10T19:32:50Z","timestamp":1544470370000},"page":"197-210","source":"Crossref","is-referenced-by-count":2,"title":["Knowledge Completion for Generics using Guided Tensor Factorization"],"prefix":"10.1162","volume":"6","author":[{"given":"Hanie","family":"Sedghi","sequence":"first","affiliation":[{"name":"Google Brain, Mountain View, CA, U.S.A.,"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ashish","family":"Sabharwal","sequence":"additional","affiliation":[{"name":"Allen Institute for Artificial Intelligence (AI2), Seattle, WA, U.S.A.,"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"281","reference":[{"key":"p_6","doi-asserted-by":"crossref","first-page":"233","DOI":"10.1162\/tacl_a_00058","volume":"5","author":"Dalvi Bhavana","year":"2017","journal-title":"TACL"},{"issue":"1","key":"p_17","first-page":"1","volume":"117","author":"Leslie Sarah-Jane","year":"2008","journal-title":"Pholosophical Review"},{"issue":"11","key":"p_19","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1145\/219717.219748","volume":"38","author":"Miller George A.","year":"1995","journal-title":"Communications of the ACM"},{"issue":"1","key":"p_21","doi-asserted-by":"crossref","first-page":"265","DOI":"10.1007\/BF01588971","volume":"14","author":"Nemhauser George L.","year":"1978","journal-title":"Mathematical Programming"},{"issue":"1","key":"p_23","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1109\/JPROC.2015.2483592","volume":"104","author":"Nickel Maximilian","year":"2016","journal-title":"Proceedings of the IEEE"}],"container-title":["Transactions of the Association for Computational Linguistics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mitpressjournals.org\/doi\/pdf\/10.1162\/tacl_a_00015","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,3,12]],"date-time":"2021-03-12T21:37:53Z","timestamp":1615585073000},"score":1,"resource":{"primary":{"URL":"https:\/\/direct.mit.edu\/tacl\/article\/43429"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,12]]},"references-count":5,"alternative-id":["10.1162\/tacl_a_00015"],"URL":"https:\/\/doi.org\/10.1162\/tacl_a_00015","relation":{},"ISSN":["2307-387X"],"issn-type":[{"value":"2307-387X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,12]]}}}