@InProceedings{freitag-kalmar-yeh:2017:BioNLP,
  author    = {Freitag, Dayne  and  Kalmar, Paul  and  Yeh, Eric},
  title     = {Discourse-Wide Extraction of Assay Frames from the Biological Literature},
  booktitle = {Proceedings of the Biomedical NLP Workshop associated with RANLP 2017},
  month     = {September},
  year      = {2017},
  address   = {Varna, Bulgaria},
  publisher = {INCOMA Ltd.},
  pages     = {15--23},
  abstract  = {We consider the problem of populating multi-part knowledge frames
	  from textual information distributed over multiple sentences in a
	  document.  We present a corpus constructed by aligning papers from
	  the cellular signaling literature to a collection of approximately
	  50,000 reference frames curated by hand as part of a decade-long
	  project. We present and evaluate two approaches to the challenging
	  problem of reconstructing these frames, which formalize biological
	  assays described in the literature.  One approach is based on
	  classifying candidate records nominated by sentence-local entity
	  co-occurrence. In the second approach, we introduce a novel virtual register
	  machine traverses an article and generates frames, trained on our
	  reference data. Our evaluations show that success in the
	  task ultimately hinges on an integration of evidence spread across
	  the discourse.},
  url       = {https://doi.org/10.26615/978-954-452-044-1_003}
}