---
title: "KBQA: An Online Template Based Question Answering System over Freebase"
authors:
  - "Wanyun Cui"
  - "Yanghua Xiao"
  - "Wei Wang"
doi: ""
url: "https://ijcai.org/proceedings/2016/640"
pdf: "https://ijcai.org/proceedings/2016/0640.pdf"
venue: "Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence"
year: 2016
pages: "4240-4240"
track: ""
keywords:
---

# KBQA: An Online Template Based Question Answering System over Freebase

Wanyun Cui, Yanghua Xiao, Wei Wang

*Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence*, pages 4240-4240.

## 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.