Abstract
The 2020 Shared Task at the Conference for Computational Language Learning (CoNLL) was devoted to Meaning Representation Parsing (MRP) across frameworks and languages. Extending a similar setup from the previous year, five distinct approaches to the representation of sentence meaning in the form of directed graphs were represented in the English training and evaluation data for the task, packaged in a uniform graph abstraction and serialization; for four of these representation frameworks, additional training and evaluation data was provided for one additional language per framework. The task received submissions from eight teams, of which two do not participate in the official ranking because they arrived after the closing deadline or made use of additional training data. 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 |
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Title of host publication | Proceedings of the CoNLL 2020 Shared Task |
Subtitle of host publication | Cross-Framework Meaning Representation Parsing |
Editors | Stephan Oepen, Omri Abend, Lasha Abzianidze, Johan Bos, Jan Hajič, Daniel Hershcovich, Bin Li, Tim O'Gorman, Nianwen Xue, Daniel Zeman |
Place of Publication | Online |
Publisher | Association for Computational Linguistics (ACL) |
Pages | 1-22 |
Number of pages | 22 |
ISBN (Electronic) | 978-1-952148-64-4 |
DOIs | |
State | Published - Nov 2020 |
Event | CoNLL 2020 Shared Task: Cross-Framework Meaning Representation Parsing - Online Duration: 19 Nov 2020 → 20 Nov 2020 http://mrp.nlpl.eu/2020/index.php |
Conference
Conference | CoNLL 2020 Shared Task |
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Period | 19/11/20 → 20/11/20 |
Internet address |
Keywords
- Computational Language Learning
- CoNLL
- Meaning Representation Parsing
- MRP
- sentence meaning