KBQA: An Online Template Based Question Answering System over Freebase

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. PDF

Cite

Text

Cui et al. "KBQA: An Online Template Based Question Answering System over Freebase." International Joint Conference on Artificial Intelligence, 2016.

Markdown

[Cui et al. "KBQA: An Online Template Based Question Answering System over Freebase." International Joint Conference on Artificial Intelligence, 2016.](https://mlanthology.org/ijcai/2016/cui2016ijcai-kbqa/)

BibTeX

@inproceedings{cui2016ijcai-kbqa,
  title     = {{KBQA: An Online Template Based Question Answering System over Freebase}},
  author    = {Cui, Wanyun and Xiao, Yanghua and Wang, Wei},
  booktitle = {International Joint Conference on Artificial Intelligence},
  year      = {2016},
  pages     = {4240-4241},
  url       = {https://mlanthology.org/ijcai/2016/cui2016ijcai-kbqa/}
}