{"type":"ScholarlyArticle","title":"KBQA: An Online Template Based Question Answering System over Freebase","authors":[{"name":"Wanyun Cui","slug":"wanyun-cui","given":"Wanyun","family":"Cui","affiliation":""},{"name":"Yanghua Xiao","slug":"yanghua-xiao","given":"Yanghua","family":"Xiao","affiliation":""},{"name":"Wei Wang","slug":"wei-wang","given":"Wei","family":"Wang","affiliation":""}],"abstract":"Question answering (QA) has become a popular way for humans to access billion-scale knowledge bases. QA systems over knowledge bases produce accurate and concise answers. The key of QA over knowledge bases is to map the question to a certain substructure in the knowledge base. To do this, KBQA (Question Answering over Knowledge Bases) uses a new kind of question representation: templates, learned from a million scale QA corpora. For example, for questions about a city's population, KBQA learns templates such as What's the population of $city?, How many people are there in $city?. It learns overall 1171303 templates for 4690 relations. Based on these templates, KBQA effectively and efficiently supports binary factoid questions or complex questions.","doi":null,"url":"https://ijcai.org/proceedings/2016/640","pdf":"https://ijcai.org/proceedings/2016/0640.pdf","markdown":"https://ijcai.org/proceedings/2016/640.md","bibtex":"https://ijcai.org/proceedings/2016/bibtex/640","volume":{"slug":"2016","title":"Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2016","url":"https://ijcai.org/proceedings/2016/","year":2016,"location":"New York, NY, USA","dates":"9–15 July 2016","editors":"Subbarao Kambhampati","isbn":"978-1-57735-770-4; 978-1-57735-771-1","publisher":"AAAI Press / International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":null,"track":"","number":640,"pages":{"first":4240,"last":4240},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}