2018
ACL
ACL 2018
Generalized chart constraints for efficient PCFG and TAG parsing
Abstract
AbstractChart constraints, which specify at which string positions a constituent may begin or end, have been shown to speed up chart parsers for PCFGs. We generalize chart constraints to more expressive grammar formalisms and describe a neural tagger which predicts chart constraints at very high precision. Our constraints accelerate both PCFG and TAG parsing, and combine effectively with other pruning techniques (coarse-to-fine and supertagging) for an overall speedup of two orders of magnitude, while improving accuracy.
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Interdisciplinary Bridge
— Deep Learning and Machine Learning and Natural Language Processing
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Trend Setter
— Natural Language Processing
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Keyword Pioneer
— chart constraint
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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, Security & Privacy, Speech & Audio
Authors
Topics
Machine Learning > Optimization & Theory > Optimization
Machine Learning > Application Areas > Efficient Computing
Deep Learning > Architectures > Neural Networks
Natural Language Processing
Natural Language Processing > Understanding > Parsing
Machine Learning > Core Methods > Optimization
Natural Language Processing > Applications > Natural Language Processing