@InProceedings{boullosa-EtAl:2018:Demos,
  author    = {Boullosa, Beto  and  Eckart de Castilho, Richard  and  Kumar, Naveen  and  Klie, Jan-Christoph  and  Gurevych, Iryna},
  title     = {Integrating Knowledge-Supported Search into the INCEpTION Annotation Platform},
  booktitle = {Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing: System Demonstrations},
  month     = {November},
  year      = {2018},
  address   = {Brussels, Belgium},
  publisher = {Association for Computational Linguistics},
  pages     = {127--132},
  abstract  = {Annotating entity mentions and linking them to a knowledge resource are essential tasks in many domains. It disambiguates mentions, introduces cross-document coreferences, and the resources contribute extra information, e.g. taxonomic relations. Such tasks benefit from text annotation tools that integrate a search which covers the text, the annotations, as well as the knowledge resource. However, to the best of our knowledge, no current tools integrate knowledge-supported search as well as entity linking support. We address this gap by introducing knowledge-supported search functionality into the INCEpTION text annotation platform. In our approach, cross-document references are created by linking entity mentions to a knowledge base in the form of a structured hierarchical vocabulary. The resulting annotations are then indexed to enable fast and yet complex queries taking into account the text, the annotations, and the vocabulary structure.},
  url       = {http://www.aclweb.org/anthology/D18-2022}
}