@InProceedings{ogorman-EtAl:2018:C18-1,
  author    = {O'Gorman, Tim  and  Regan, Michael  and  Griffitt, Kira  and  Hermjakob, Ulf  and  Knight, Kevin  and  Palmer, Martha},
  title     = {AMR Beyond the Sentence: the Multi-sentence AMR corpus},
  booktitle = {Proceedings of the 27th International Conference on Computational Linguistics},
  month     = {August},
  year      = {2018},
  address   = {Santa Fe, New Mexico, USA},
  publisher = {Association for Computational Linguistics},
  pages     = {3693--3702},
  abstract  = {There are few corpora that endeavor to represent the semantic content of entire documents. We present a corpus that accomplishes one way of capturing document level semantics, by annotating coreference and similar phenomena (bridging and implicit roles) on top of gold Abstract Meaning Representations of sentence-level semantics. We present a new corpus of this annotation, with analysis of its quality, alongside a plausible baseline for comparison. It is hoped that this Multi-Sentence AMR corpus (MS-AMR) may become a feasible method for developing rich representations of document meaning, useful for tasks such as information extraction and question answering.},
  url       = {http://www.aclweb.org/anthology/C18-1313}
}