Revisiting Higher-Order Dependency Parsers

ACL 2020 Erick FonsecaAndr{\'e} F. T. Martins

Neural encoders have allowed dependency parsers to shift from higher-order structured models to simpler first-order ones, making decoding faster and still achieving better accuracy than non-neural parsers. This has led to a belief that neural encoders can implicitly encode structural constraints, such as siblings and grandparents in a tree... (read more)

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