Please use this identifier to cite or link to this item:
http://hdl.handle.net/20.500.11861/7403
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Lai, Sunny | en_US |
dc.contributor.author | Lo, Chun Hei | en_US |
dc.contributor.author | Prof. LEUNG Kwong Sak | en_US |
dc.contributor.author | Leung, Yee | en_US |
dc.date.accessioned | 2023-02-22T03:16:24Z | - |
dc.date.available | 2023-02-22T03:16:24Z | - |
dc.date.issued | 2019 | - |
dc.identifier.citation | 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, 2020, pp. 104-113 | en_US |
dc.identifier.isbn | 978-195073760-4 | - |
dc.identifier.uri | https://aclanthology.org/K19-2010 | - |
dc.identifier.uri | http://hdl.handle.net/20.500.11861/7403 | - |
dc.description.abstract | This paper describes our system (RESOLVER) submitted to the CoNLL 2019 shared task on Cross-Framework Meaning Representation Parsing (MRP). Our system implements a transition-based parser with a directed acyclic graph (DAG) to tree preprocessor and a novel cross-framework variable-arity resolve action that generalizes over five different representations. Although we ranked low in the competition, we have shown the current limitations and potentials of including variable-arity action in MRP and concluded with directions for improvements in the future. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Association for Computational Linguistics | en_US |
dc.title | CUHK at MRP 2019: Transition-based parser with cross-framework variable-arity resolve action | en_US |
dc.type | Conference Paper | en_US |
dc.relation.conference | 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 | en_US |
dc.identifier.doi | 10.18653/v1/K19-2010 | - |
item.fulltext | No Fulltext | - |
crisitem.author.dept | Department of Applied Data Science | - |
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