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.
Cite
CITATION STYLE
Lai, S., Lo, C. H., Leung, K. S., & Leung, Y. (2020). CUHK at MRP 2019: Transition-based parser with cross-framework variable-arity resolve action. 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. 104–113). Association for Computational Linguistics. https://doi.org/10.18653/v1/K19-2010
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.