@InProceedings{kollar-EtAl:2018:N18-3,
  author    = {Kollar, Thomas  and  Berry, Danielle  and  Stuart, Lauren  and  Owczarzak, Karolina  and  Chung, Tagyoung  and  Mathias, Lambert  and  Kayser, Michael  and  Snow, Bradford  and  Matsoukas, Spyros},
  title     = {The Alexa Meaning Representation Language},
  booktitle = {Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 3 (Industry Papers)},
  month     = {June},
  year      = {2018},
  address   = {New Orleans - Louisiana},
  publisher = {Association for Computational Linguistics},
  pages     = {177--184},
  abstract  = {This paper introduces a meaning representation for spoken language understanding. The Alexa meaning representation language (AMRL), unlike previous approaches, which factor spoken utterances into domains, provides a common representation for how people communicate in spoken language. AMRL is a rooted graph, links to a large-scale ontology, supports cross-domain queries, fine-grained types, complex utterances and composition. A spoken language dataset has been collected for Alexa, which contains ∼20k examples across eight domains. A version of this meaning representation was released to developers at a trade show in 2016.},
  url       = {http://www.aclweb.org/anthology/N18-3022}
}