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MRP 2019: Cross-Framework Meaning Representation Parsing
University of Oslo.
The Hebrew University of Jerusalem.
Charles University in Prague.
University of Copenhagen.
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2019 (English)In: Proceedings of the Shared Task on Cross-Framework Meaning Representation Parsing at the 2019 Conference on Natural Language Learning, Association for Computational Linguistics , 2019, p. 1-27Conference paper, Published paper (Other academic)
Abstract [en]

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

Place, publisher, year, edition, pages
Association for Computational Linguistics , 2019. p. 1-27
National Category
Language Technology (Computational Linguistics)
Identifiers
URN: urn:nbn:se:liu:diva-168626DOI: 10.18653/v1/K19-2001ISBN: 978-1-950737-60-4 (print)OAI: oai:DiVA.org:liu-168626DiVA, id: diva2:1461490
Conference
Shared Task on Cross-Framework Meaning Representation Parsing at the 2019 Conference on Natural Language Learning
Available from: 2020-08-26 Created: 2020-08-26 Last updated: 2020-08-26

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Publisher's full texthttps://www.aclweb.org/anthology/K19-2001

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Kuhlmann, Marco

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CiteExportLink to record
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Citation style
  • apa
  • ieee
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  • vancouver
  • oxford
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Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf