2019
ACL
ACL 2019
Parsing Meaning Representations: Is Easier Always Better?
Abstract
AbstractThe parsing accuracy varies a great deal for different meaning representations. In this paper, we compare the parsing performances between Abstract Meaning Representation (AMR) and Minimal Recursion Semantics (MRS), and provide an in-depth analysis of what factors contributed to the discrepancy in their parsing accuracy. By crystalizing the trade-off between representation expressiveness and ease of automatic parsing, we hope our results can help inform the design of the next-generation meaning representations.
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The Questioner
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Interdisciplinary Bridge
— Interdisciplinary and Natural Language Processing
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Keyword Pioneer
— minimal recursion semantics
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio
Authors
Topics
Natural Language Processing > Understanding > Parsing
Natural Language Processing > Understanding > Semantic Analysis
Natural Language Processing > Resources & Methods > Lexical Semantics
Interdisciplinary > Linguistics > Computational Linguistics
Natural Language Processing > Understanding > Semantics