Year: 2019
Type: article
Abstract: We extend a state-of-the-art deep neural architecture for semantic dependency parsing with features defined over syntactic dependency trees.Our empirical results show that only gold-standard syntactic information leads to consistent improvements in semantic parsing accuracy, and that the magnitude of these improvements varies with the specific combination of the syntactic and the semantic representation used.In contrast, automatically predicted syntax does not seem to help semantic parsing.Our error analysis suggests that there is a significant overlap between syntactic and semantic representations.
Authors: Robin Kurtz, Daniel Roxbo, Marco Kuhlmann
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W3086398705