@InProceedings{wolfe-dredze-vandurme:2017:Short,
  author    = {Wolfe, Travis  and  Dredze, Mark  and  Van Durme, Benjamin},
  title     = {Pocket Knowledge Base Population},
  booktitle = {Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)},
  month     = {July},
  year      = {2017},
  address   = {Vancouver, Canada},
  publisher = {Association for Computational Linguistics},
  pages     = {305--310},
  abstract  = {Existing Knowledge Base Population methods extract relations from a closed
	relational schema with limited coverage leading to sparse KBs. We propose
	Pocket Knowledge Base Population (PKBP), the task of dynamically constructing a
	KB of entities related to a query and finding the best characterization of
	relationships between entities. We describe novel Open Information Extraction
	methods which leverage the PKB to find informative trigger words. We evaluate
	using existing KBP shared-task data as well anew annotations collected for this
	work. Our methods produce high quality KB from just text with many more
	entities and relationships than existing KBP systems.},
  url       = {http://aclweb.org/anthology/P17-2048}
}