MRP 2019: Cross-Framework Meaning Representation Parsing

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Documents

  • Stephan Oepen
  • Omri Abend
  • Jan Hajic
  • Hershcovich, Daniel
  • Marco Kuhlmann
  • Tim O’gorman
  • Nianwen Xue
  • Jayeol Chun
  • Milan Straka
  • Zdenka Uresova
The 2019 Shared Task at the Conference for Computational Language Learning (CoNLL) was devoted to Meaning Representation Parsing (MRP) across frameworks. Five distinct approaches to the representation of sentence meaning in the form of directed graph were represented in the training and evaluation data for the task, packaged in a uniform abstract graph representation and serialization. The task received submissions from eighteen teams, of which five do not participate in the official ranking because they arrived after the closing deadline, made use of additional training data, or involved one of the task co-organizers. All technical information regarding the task, including system submissions, official results, and links to supporting resources and software are available from the task web site at: http://mrp.nlpl.eu
Original languageEnglish
Title of host publicationProceedings of the Shared Task on Cross-Framework Meaning Representation Parsing at the 2019 Conference on Natural Language Learning
PublisherAssociation for Computational Linguistics
Publication date2020
Pages1-27
ISBN (Electronic)978-1-950737-60-4
DOIs
Publication statusPublished - 2020
Event2019 Conference on Natural Language Learning, CoNLL - Hong Kong, China
Duration: 1 Nov 20191 Nov 2019

Conference

Conference2019 Conference on Natural Language Learning, CoNLL
LandChina
ByHong Kong
Periode01/11/201901/11/2019

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