{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,11]],"date-time":"2026-01-11T04:45:24Z","timestamp":1768106724530,"version":"3.49.0"},"reference-count":9,"publisher":"Association for Computing Machinery (ACM)","issue":"12","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Proc. VLDB Endow."],"published-print":{"date-parts":[[2022,8]]},"abstract":"<jats:p>In recent years, a significant number of question answering (QA) systems that retrieve answers to natural language questions from knowledge graphs (KG) have been introduced. However, finding a benchmark that accurately evaluates the quality of a question answering system is a difficult task because of (1) the high degree of variations with respect to the fine-grained properties among the available benchmarks, (2) the static nature of the available benchmarks versus the evolving nature of KGs, and (3) the limited number of KGs targeted by existing benchmarks, which hinders the usability of QA systems in real deployment over KGs that are different from those which the QA system was evaluated using. In this demonstration, we introduce SmartBench, an automatic benchmark generating system for QA over any KG. The benchmark generated by SmartBench is guaranteed to cover all the properties of the natural language questions and queries that were encountered in the literature as long as the targeted KG includes these properties.<\/jats:p>","DOI":"10.14778\/3554821.3554869","type":"journal-article","created":{"date-parts":[[2022,9,29]],"date-time":"2022-09-29T22:28:39Z","timestamp":1664490519000},"page":"3662-3665","source":"Crossref","is-referenced-by-count":3,"title":["SmartBench"],"prefix":"10.14778","volume":"15","author":[{"given":"Abdelghny","family":"Orogat","sequence":"first","affiliation":[{"name":"Carleton University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ahmed","family":"El-Roby","sequence":"additional","affiliation":[{"name":"Carleton University"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2022,9,29]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-76298-0_52"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.5555\/2898607.2898816"},{"key":"e_1_2_1_3_1","volume-title":"Survey on challenges of question answering in the semantic web. Semantic Web, 8(6)","author":"H\u00f6ffner K.","year":"2017","unstructured":"K. H\u00f6ffner , S. Walter , E. Marx , R. Usbeck , J. Lehmann , and A.-C. Ngonga Ngomo . Survey on challenges of question answering in the semantic web. Semantic Web, 8(6) , 2017 . K. H\u00f6ffner, S. Walter, E. Marx, R. Usbeck, J. Lehmann, and A.-C. Ngonga Ngomo. Survey on challenges of question answering in the semantic web. Semantic Web, 8(6), 2017."},{"key":"e_1_2_1_4_1","volume-title":"CBench: Demonstrating Comprehensive Evaluation of Question Answering Systems over Knowledge Graphs Through Deep Analysis of Benchmarks. PVLDB, 14(12)","author":"Orogat A.","year":"2021","unstructured":"A. Orogat and A. El-Roby . CBench: Demonstrating Comprehensive Evaluation of Question Answering Systems over Knowledge Graphs Through Deep Analysis of Benchmarks. PVLDB, 14(12) , 2021 . A. Orogat and A. El-Roby. CBench: Demonstrating Comprehensive Evaluation of Question Answering Systems over Knowledge Graphs Through Deep Analysis of Benchmarks. PVLDB, 14(12), 2021."},{"key":"e_1_2_1_5_1","volume-title":"CBench: Towards Better Evaluation of Question Answering Over Knowledge Graphs. PVLDB, 14(8)","author":"Orogat A.","year":"2021","unstructured":"A. Orogat , I. Liu , and A. El-Roby . CBench: Towards Better Evaluation of Question Answering Over Knowledge Graphs. PVLDB, 14(8) , 2021 . A. Orogat, I. Liu, and A. El-Roby. CBench: Towards Better Evaluation of Question Answering Over Knowledge Graphs. PVLDB, 14(8), 2021."},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/1242572.1242667"},{"key":"e_1_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-68204-4_22"},{"key":"e_1_2_1_8_1","volume-title":"Joint Workshop on NLIWoD and Question Answering over Linked Data challenge","author":"Usbeck R.","year":"2018","unstructured":"R. Usbeck , R. H. Gusmita , M. Saleem , and A.-C. N. Ngomo . 9th challenge on question answering over linked data (QALD-9) . Joint Workshop on NLIWoD and Question Answering over Linked Data challenge , 2018 . R. Usbeck, R. H. Gusmita, M. Saleem, and A.-C. N. Ngomo. 9th challenge on question answering over linked data (QALD-9). Joint Workshop on NLIWoD and Question Answering over Linked Data challenge, 2018."},{"key":"e_1_2_1_9_1","volume-title":"Wikidata: a free collaborative knowledgebase. Communications of the ACM, 57(10)","author":"Vrande\u010di\u0107 D.","year":"2014","unstructured":"D. Vrande\u010di\u0107 and M. Kr\u00f6tzsch . Wikidata: a free collaborative knowledgebase. Communications of the ACM, 57(10) , 2014 . D. Vrande\u010di\u0107 and M. Kr\u00f6tzsch. Wikidata: a free collaborative knowledgebase. Communications of the ACM, 57(10), 2014."}],"container-title":["Proceedings of the VLDB Endowment"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.14778\/3554821.3554869","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,28]],"date-time":"2022-12-28T11:33:10Z","timestamp":1672227190000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.14778\/3554821.3554869"}},"subtitle":["demonstrating automatic generation of comprehensive benchmarks for question answering over knowledge graphs"],"short-title":[],"issued":{"date-parts":[[2022,8]]},"references-count":9,"journal-issue":{"issue":"12","published-print":{"date-parts":[[2022,8]]}},"alternative-id":["10.14778\/3554821.3554869"],"URL":"https:\/\/doi.org\/10.14778\/3554821.3554869","relation":{},"ISSN":["2150-8097"],"issn-type":[{"value":"2150-8097","type":"print"}],"subject":[],"published":{"date-parts":[[2022,8]]}}}