@InProceedings{abujabal-EtAl:2017:EMNLP2017Demos,
  author    = {Abujabal, Abdalghani  and  Saha Roy, Rishiraj  and  Yahya, Mohamed  and  Weikum, Gerhard},
  title     = {QUINT: Interpretable Question Answering over Knowledge Bases},
  booktitle = {Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing: System Demonstrations},
  month     = {September},
  year      = {2017},
  address   = {Copenhagen, Denmark},
  publisher = {Association for Computational Linguistics},
  pages     = {61--66},
  abstract  = {We present QUINT, a live system for question answering over knowledge bases.
	QUINT automatically learns role-aligned utterance-query templates from user
	questions paired with their answers. When QUINT answers a question, it
	visualizes the complete derivation sequence from the natural language utterance
	to the final answer. The derivation provides an explanation of how the
	syntactic structure of the question was used to derive the structure of a
	SPARQL query, and how the phrases in the question were used to instantiate
	different parts of the query. When an answer seems unsatisfactory, the
	derivation provides valuable insights towards reformulating the question.},
  url       = {http://www.aclweb.org/anthology/D17-2011}
}