@inproceedings{oepen-etal-2019-mrp,
title = "{MRP} 2019: Cross-Framework Meaning Representation Parsing",
author = "Oepen, Stephan and
Abend, Omri and
Hajic, Jan and
Hershcovich, Daniel and
Kuhlmann, Marco and
O{'}Gorman, Tim and
Xue, Nianwen and
Chun, Jayeol and
Straka, Milan and
Uresova, Zdenka",
booktitle = "Proceedings of the Shared Task on Cross-Framework Meaning Representation Parsing at the 2019 Conference on Natural Language Learning",
month = nov,
year = "2019",
address = "Hong Kong",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/K19-2001",
doi = "10.18653/v1/K19-2001",
pages = "1--27",
abstract = "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",
}
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<abstract>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</abstract>
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%0 Conference Proceedings
%T MRP 2019: Cross-Framework Meaning Representation Parsing
%A Oepen, Stephan
%A Abend, Omri
%A Hajic, Jan
%A Hershcovich, Daniel
%A Kuhlmann, Marco
%A O’Gorman, Tim
%A Xue, Nianwen
%A Chun, Jayeol
%A Straka, Milan
%A Uresova, Zdenka
%S Proceedings of the Shared Task on Cross-Framework Meaning Representation Parsing at the 2019 Conference on Natural Language Learning
%D 2019
%8 nov
%I Association for Computational Linguistics
%C Hong Kong
%F oepen-etal-2019-mrp
%X 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
%R 10.18653/v1/K19-2001
%U https://aclanthology.org/K19-2001
%U https://doi.org/10.18653/v1/K19-2001
%P 1-27
Markdown (Informal)
[MRP 2019: Cross-Framework Meaning Representation Parsing](https://aclanthology.org/K19-2001) (Oepen et al., CoNLL 2019)
ACL
- Stephan Oepen, Omri Abend, Jan Hajic, Daniel Hershcovich, Marco Kuhlmann, Tim O’Gorman, Nianwen Xue, Jayeol Chun, Milan Straka, and Zdenka Uresova. 2019. MRP 2019: Cross-Framework Meaning Representation Parsing. In Proceedings of the Shared Task on Cross-Framework Meaning Representation Parsing at the 2019 Conference on Natural Language Learning, pages 1–27, Hong Kong. Association for Computational Linguistics.