Annotations Matter: Leveraging Multi-task Learning to Parse UD and SUD

Zeeshan Ali Sayyed, Daniel Dakota


Anthology ID:
2021.findings-acl.305
Volume:
Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
Month:
August
Year:
2021
Address:
Online
Editors:
Chengqing Zong, Fei Xia, Wenjie Li, Roberto Navigli
Venue:
Findings
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
3467–3481
Language:
URL:
https://aclanthology.org/2021.findings-acl.305
DOI:
10.18653/v1/2021.findings-acl.305
Bibkey:
Cite (ACL):
Zeeshan Ali Sayyed and Daniel Dakota. 2021. Annotations Matter: Leveraging Multi-task Learning to Parse UD and SUD. In Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021, pages 3467–3481, Online. Association for Computational Linguistics.
Cite (Informal):
Annotations Matter: Leveraging Multi-task Learning to Parse UD and SUD (Sayyed & Dakota, Findings 2021)
Copy Citation:
PDF:
https://preview.aclanthology.org/nschneid-patch-4/2021.findings-acl.305.pdf
Video:
 https://preview.aclanthology.org/nschneid-patch-4/2021.findings-acl.305.mp4
Data
Universal Dependencies