2019
EMNLP
EMNLP 2019
Realizing Universal Dependencies Structures
Abstract
AbstractWe first describe a surface realizer forUniversal Dependencies (UD) structures. The system uses a symbolic approach to transform the dependency tree into a tree of constituents that is transformed into an English sentence by an existing realizer. This approach was then adapted for the two shared tasks of SR’19. The system is quite fast and showed competitive results for English sentences using automatic and manual evaluation measures.
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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