Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.11861/7403
Title: CUHK at MRP 2019: Transition-based parser with cross-framework variable-arity resolve action
Authors: Lai, Sunny 
Lo, Chun Hei 
Prof. LEUNG Kwong Sak 
Leung, Yee 
Issue Date: 2019
Publisher: Association for Computational Linguistics
Source: 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
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 
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.
Type: Conference Paper
URI: https://aclanthology.org/K19-2010
http://hdl.handle.net/20.500.11861/7403
ISBN: 978-195073760-4
DOI: 10.18653/v1/K19-2010
Appears in Collections:Applied Data Science - Publication

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