Abstract
We design, implement and evaluate two semantic parsers, which represent factorization- and composition-based approaches respectively, for Elementary Dependency Structures (EDS) at the CoNLL 2019 Shared Task on Cross-Framework Meaning Representation Parsing. The detailed evaluation of the two parsers gives us a new perception about parsing into linguistically enriched meaning representations: current neural EDS parsers are able to reach an accuracy at the inter-annotator agreement level in the same-epoch- and-domain setup.
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CITATION STYLE
Chen, Y., Ye, Y., & Sun, W. (2020). Peking at MRP 2019: Factorization- And composition-based parsing for elementary dependency structures. 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. 166–176). Association for Computational Linguistics. https://doi.org/10.18653/v1/K19-2016
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