Please use this identifier to cite or link to this item: doi:10.22028/D291-36125
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Title: Compositional Semantic Parsing across Graphbanks
Author(s): Lindemann, Matthias
Groschwitz, Jonas
Koller, Alexander
Editor(s): Nakov, Preslav
Palmer, Alexis
Language: English
Title: The 57th Annual Meeting of the Association for Computational Linguistics - tutorial abstracts : July 28, 2019, Florene, Italy : ACL 2019
Startpage: 4576
Endpage: 4585
Publisher/Platform: Association for Computational Linguistics
Year of Publication: 2019
Title of the Conference: ACL 2019
Place of the conference: Florence, Italy
Publikation type: Conference Paper
Abstract: Most semantic parsers that map sentences to graph-based meaning representations are hand-designed for specific graphbanks. We present a compositional neural semantic parser which achieves, for the first time, competitive accuracies across a diverse range of graphbanks. Incorporating BERT embeddings and multi-task learning improves the accuracy further, setting new states of the art on DM, PAS, PSD, AMR 2015 and EDS.
DOI of the first publication: 10.18653/v1/P19-1450
URL of the first publication: https://aclanthology.org/P19-1450.pdf
Link to this record: hdl:20.500.11880/32899
http://dx.doi.org/10.22028/D291-36125
ISBN: 978-1-950737-50-5
Date of registration: 10-May-2022
Faculty: P - Philosophische Fakultät
Department: P - Sprachwissenschaft und Sprachtechnologie
Professorship: P - Prof. Dr. Alexander Koller
Collections:SciDok - Der Wissenschaftsserver der Universität des Saarlandes

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