@InProceedings{heinzerling-strube-lin:2017:EACLlong,
  author    = {Heinzerling, Benjamin  and  Strube, Michael  and  Lin, Chin-Yew},
  title     = {Trust, but Verify! Better Entity Linking through Automatic Verification},
  booktitle = {Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers},
  month     = {April},
  year      = {2017},
  address   = {Valencia, Spain},
  publisher = {Association for Computational Linguistics},
  pages     = {828--838},
  abstract  = {We introduce automatic verification as a post-processing step for entity
	linking (EL).
	The proposed method trusts EL system results collectively, by assuming entity
	mentions are mostly linked correctly, in order to create a semantic profile of
	the given text using geospatial and temporal information, as well as
	fine-grained entity types.
	This profile is then used to automatically verify each linked mention
	individually, i.e., to predict whether it has been linked correctly or not.
	Verification allows leveraging a rich set of global and pairwise features that
	would be prohibitively expensive for EL systems employing global inference.
	Evaluation shows consistent improvements across datasets and systems. In
	particular, when applied to state-of-the-art systems, our method yields an
	absolute improvement in linking performance of up to 1.7 F1 on AIDA/CoNLL'03
	and up to 2.4 F1 on the English TAC KBP 2015 TEDL dataset.},
  url       = {http://www.aclweb.org/anthology/E17-1078}
}