MRP 2019: Cross-framework meaning representation parsing

Stephan Oepen; Omri Abend; Jan Hajič; Daniel Hershcovich; Marco Kuhlmann; Tim O'Gorman; Nianwen Xue; Jayeol Chun; Milan Straka; Zdeňka Urešová

doi:10.18653/v1/K19-2001

MRP 2019: Cross-framework meaning representation parsing

Stephan Oepen, Omri Abend, Jan Hajič, Daniel Hershcovich, Marco Kuhlmann, Tim O'Gorman, Nianwen Xue, Jayeol Chun, Milan Straka, Zdeňka Urešová^*

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

63 Scopus citations

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 graphs were represented in the training and evaluation data for the task, packaged in a uniform graph abstraction 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 extra 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 language	English
Title of host publication	CoNLL 2019 - SIGNLL Conference on Computational Natural Language Learning, Proceedings of the Shared Task on Cross-Framework Meaning Representation Parsing at the 2019 Conference on Natural Language Learning
Publisher	Association for Computational Linguistics
Pages	1-27
Number of pages	27
ISBN (Electronic)	9781950737604
DOIs	https://doi.org/10.18653/v1/K19-2001
State	Published - 2020
Event	2019 Shared Task on Cross-Framework Meaning Representation Parsing, MRP 2019 at the 23rd Conference for Computational Language Learning, CoNLL 2019 - Hong Kong, China Duration: 3 Nov 2019 → …

Publication series

Name	CoNLL 2019 - SIGNLL Conference on Computational Natural Language Learning, Proceedings of the Shared Task on Cross-Framework Meaning Representation Parsing at the 2019 Conference on Natural Language Learning

Conference

Conference	2019 Shared Task on Cross-Framework Meaning Representation Parsing, MRP 2019 at the 23rd Conference for Computational Language Learning, CoNLL 2019
Country/Territory	China
City	Hong Kong
Period	3/11/19 → …

Bibliographical note

Publisher Copyright:
© 2019 Association for Computational Linguistics

Access to Document

10.18653/v1/K19-2001

Cite this

Oepen, S., Abend, O., Hajič, J., Hershcovich, D., Kuhlmann, M., O'Gorman, T., Xue, N., Chun, J., Straka, M., & Urešová, Z. (2020). MRP 2019: Cross-framework meaning representation parsing. In CoNLL 2019 - SIGNLL Conference on Computational Natural Language Learning, Proceedings of the Shared Task on Cross-Framework Meaning Representation Parsing at the 2019 Conference on Natural Language Learning (pp. 1-27). (CoNLL 2019 - SIGNLL Conference on Computational Natural Language Learning, Proceedings of the Shared Task on Cross-Framework Meaning Representation Parsing at the 2019 Conference on Natural Language Learning). Association for Computational Linguistics. https://doi.org/10.18653/v1/K19-2001

Oepen, Stephan ; Abend, Omri ; Hajič, Jan et al. / MRP 2019 : Cross-framework meaning representation parsing. CoNLL 2019 - SIGNLL Conference on Computational Natural Language Learning, Proceedings of the Shared Task on Cross-Framework Meaning Representation Parsing at the 2019 Conference on Natural Language Learning. Association for Computational Linguistics, 2020. pp. 1-27 (CoNLL 2019 - SIGNLL Conference on Computational Natural Language Learning, Proceedings of the Shared Task on Cross-Framework Meaning Representation Parsing at the 2019 Conference on Natural Language Learning).

@inproceedings{b0f38ec17ac94262a1889e304780e334,

title = "MRP 2019: Cross-framework meaning representation parsing",

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 graphs were represented in the training and evaluation data for the task, packaged in a uniform graph abstraction 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 extra 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.",

author = "Stephan Oepen and Omri Abend and Jan Haji{\v c} and Daniel Hershcovich and Marco Kuhlmann and Tim O'Gorman and Nianwen Xue and Jayeol Chun and Milan Straka and Zde{\v n}ka Ure{\v s}ov{\'a}",

note = "Publisher Copyright: {\textcopyright} 2019 Association for Computational Linguistics; 2019 Shared Task on Cross-Framework Meaning Representation Parsing, MRP 2019 at the 23rd Conference for Computational Language Learning, CoNLL 2019 ; Conference date: 03-11-2019",

year = "2020",

doi = "10.18653/v1/K19-2001",

language = "אנגלית",

series = "CoNLL 2019 - SIGNLL Conference on Computational Natural Language Learning, Proceedings of the Shared Task on Cross-Framework Meaning Representation Parsing at the 2019 Conference on Natural Language Learning",

publisher = "Association for Computational Linguistics",

pages = "1--27",

booktitle = "CoNLL 2019 - SIGNLL Conference on Computational Natural Language Learning, Proceedings of the Shared Task on Cross-Framework Meaning Representation Parsing at the 2019 Conference on Natural Language Learning",

}

Oepen, S, Abend, O, Hajič, J, Hershcovich, D, Kuhlmann, M, O'Gorman, T, Xue, N, Chun, J, Straka, M & Urešová, Z 2020, MRP 2019: Cross-framework meaning representation parsing. in CoNLL 2019 - SIGNLL Conference on Computational Natural Language Learning, Proceedings of the Shared Task on Cross-Framework Meaning Representation Parsing at the 2019 Conference on Natural Language Learning. CoNLL 2019 - SIGNLL Conference on Computational Natural Language Learning, Proceedings of the Shared Task on Cross-Framework Meaning Representation Parsing at the 2019 Conference on Natural Language Learning, Association for Computational Linguistics, pp. 1-27, 2019 Shared Task on Cross-Framework Meaning Representation Parsing, MRP 2019 at the 23rd Conference for Computational Language Learning, CoNLL 2019, Hong Kong, China, 3/11/19. https://doi.org/10.18653/v1/K19-2001

MRP 2019: Cross-framework meaning representation parsing. / Oepen, Stephan; Abend, Omri; Hajič, Jan et al.
CoNLL 2019 - SIGNLL Conference on Computational Natural Language Learning, Proceedings of the Shared Task on Cross-Framework Meaning Representation Parsing at the 2019 Conference on Natural Language Learning. Association for Computational Linguistics, 2020. p. 1-27 (CoNLL 2019 - SIGNLL Conference on Computational Natural Language Learning, Proceedings of the Shared Task on Cross-Framework Meaning Representation Parsing at the 2019 Conference on Natural Language Learning).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - MRP 2019

T2 - 2019 Shared Task on Cross-Framework Meaning Representation Parsing, MRP 2019 at the 23rd Conference for Computational Language Learning, CoNLL 2019

AU - Oepen, Stephan

AU - Abend, Omri

AU - Hajič, Jan

AU - Hershcovich, Daniel

AU - Kuhlmann, Marco

AU - O'Gorman, Tim

AU - Xue, Nianwen

AU - Chun, Jayeol

AU - Straka, Milan

AU - Urešová, Zdeňka

PY - 2020

Y1 - 2020

N2 - 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 graphs were represented in the training and evaluation data for the task, packaged in a uniform graph abstraction 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 extra 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.

AB - 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 graphs were represented in the training and evaluation data for the task, packaged in a uniform graph abstraction 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 extra 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.

UR - http://www.scopus.com/inward/record.url?scp=85084354885&partnerID=8YFLogxK

U2 - 10.18653/v1/K19-2001

DO - 10.18653/v1/K19-2001

M3 - ???researchoutput.researchoutputtypes.contributiontobookanthology.conference???

AN - SCOPUS:85084354885

T3 - CoNLL 2019 - SIGNLL Conference on Computational Natural Language Learning, Proceedings of the Shared Task on Cross-Framework Meaning Representation Parsing at the 2019 Conference on Natural Language Learning

SP - 1

EP - 27

BT - CoNLL 2019 - SIGNLL Conference on Computational Natural Language Learning, Proceedings of the Shared Task on Cross-Framework Meaning Representation Parsing at the 2019 Conference on Natural Language Learning

PB - Association for Computational Linguistics

Y2 - 3 November 2019

ER -

Oepen S, Abend O, Hajič J, Hershcovich D, Kuhlmann M, O'Gorman T et al. MRP 2019: Cross-framework meaning representation parsing. In CoNLL 2019 - SIGNLL Conference on Computational Natural Language Learning, Proceedings of the Shared Task on Cross-Framework Meaning Representation Parsing at the 2019 Conference on Natural Language Learning. Association for Computational Linguistics. 2020. p. 1-27. (CoNLL 2019 - SIGNLL Conference on Computational Natural Language Learning, Proceedings of the Shared Task on Cross-Framework Meaning Representation Parsing at the 2019 Conference on Natural Language Learning). doi: 10.18653/v1/K19-2001

MRP 2019: Cross-framework meaning representation parsing

Abstract

Publication series

Conference

Bibliographical note

Access to Document

Other files and links

Fingerprint

Cite this