CUHK at MRP 2019: Transition-Based Parser with Cross-Framework Variable-Arity Resolve Action

Sunny Lai, Chun Hei Lo, Kwong Sak Leung, Yee Leung


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.
Anthology ID:
K19-2010
Volume:
Proceedings of the Shared Task on Cross-Framework Meaning Representation Parsing at the 2019 Conference on Natural Language Learning
Month:
November
Year:
2019
Address:
Hong Kong
Editors:
Stephan Oepen, Omri Abend, Jan Hajic, Daniel Hershcovich, Marco Kuhlmann, Tim O’Gorman, Nianwen Xue
Venue:
CoNLL
SIG:
SIGNLL
Publisher:
Association for Computational Linguistics
Note:
Pages:
104–113
Language:
URL:
https://aclanthology.org/K19-2010
DOI:
10.18653/v1/K19-2010
Bibkey:
Cite (ACL):
Sunny Lai, Chun Hei Lo, Kwong Sak Leung, and Yee Leung. 2019. CUHK at MRP 2019: Transition-Based Parser with Cross-Framework Variable-Arity Resolve Action. In Proceedings of the Shared Task on Cross-Framework Meaning Representation Parsing at the 2019 Conference on Natural Language Learning, pages 104–113, Hong Kong. Association for Computational Linguistics.
Cite (Informal):
CUHK at MRP 2019: Transition-Based Parser with Cross-Framework Variable-Arity Resolve Action (Lai et al., CoNLL 2019)
Copy Citation:
PDF:
https://aclanthology.org/K19-2010.pdf
Attachment:
 K19-2010.Attachment.zip