Multi-Task Semantic Dependency Parsing with Policy Gradient for Learning Easy-First Strategies
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Multi-Task Semantic Dependency Parsing with Policy Gradient for Learning Easy-First Strategies. / Kurita, Shuhei; Søgaard, Anders.
Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, 2019. s. 2420-2430.Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
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TY - GEN
T1 - Multi-Task Semantic Dependency Parsing with Policy Gradient for Learning Easy-First Strategies
AU - Kurita, Shuhei
AU - Søgaard, Anders
PY - 2019
Y1 - 2019
N2 - In Semantic Dependency Parsing (SDP), semantic relations form directed acyclic graphs, rather than trees. We propose a new iterative predicate selection (IPS) algorithm for SDP. Our IPS algorithm combines the graph-based and transition-based parsing approaches in order to handle multiple semantic head words. We train the IPS model using a combination of multi-task learning and task-specific policy gradient training. Trained this way, IPS achieves a new state of the art on the SemEval 2015 Task 18 datasets. Furthermore, we observe that policy gradient training learns an easy-first strategy.
AB - In Semantic Dependency Parsing (SDP), semantic relations form directed acyclic graphs, rather than trees. We propose a new iterative predicate selection (IPS) algorithm for SDP. Our IPS algorithm combines the graph-based and transition-based parsing approaches in order to handle multiple semantic head words. We train the IPS model using a combination of multi-task learning and task-specific policy gradient training. Trained this way, IPS achieves a new state of the art on the SemEval 2015 Task 18 datasets. Furthermore, we observe that policy gradient training learns an easy-first strategy.
U2 - 10.18653/v1/P19-1232
DO - 10.18653/v1/P19-1232
M3 - Article in proceedings
SP - 2420
EP - 2430
BT - Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
PB - Association for Computational Linguistics
T2 - 57th Annual Meeting of the Association for Computational Linguistics
Y2 - 1 July 2019 through 1 July 2019
ER -
ID: 240408754