From Raw Text to Enhanced Universal Dependencies: The Parsing Shared Task at IWPT 2021

Gosse Bouma, Djamé Seddah, Daniel Zeman


Abstract
We describe the second IWPT task on end-to-end parsing from raw text to Enhanced Universal Dependencies. We provide details about the evaluation metrics and the datasets used for training and evaluation. We compare the approaches taken by participating teams and discuss the results of the shared task, also in comparison with the first edition of this task.
Anthology ID:
2021.iwpt-1.15
Volume:
Proceedings of the 17th International Conference on Parsing Technologies and the IWPT 2021 Shared Task on Parsing into Enhanced Universal Dependencies (IWPT 2021)
Month:
August
Year:
2021
Address:
Online
Editors:
Stephan Oepen, Kenji Sagae, Reut Tsarfaty, Gosse Bouma, Djamé Seddah, Daniel Zeman
Venue:
IWPT
SIG:
SIGPARSE
Publisher:
Association for Computational Linguistics
Note:
Pages:
146–157
Language:
URL:
https://aclanthology.org/2021.iwpt-1.15
DOI:
10.18653/v1/2021.iwpt-1.15
Bibkey:
Cite (ACL):
Gosse Bouma, Djamé Seddah, and Daniel Zeman. 2021. From Raw Text to Enhanced Universal Dependencies: The Parsing Shared Task at IWPT 2021. In Proceedings of the 17th International Conference on Parsing Technologies and the IWPT 2021 Shared Task on Parsing into Enhanced Universal Dependencies (IWPT 2021), pages 146–157, Online. Association for Computational Linguistics.
Cite (Informal):
From Raw Text to Enhanced Universal Dependencies: The Parsing Shared Task at IWPT 2021 (Bouma et al., IWPT 2021)
Copy Citation:
PDF:
https://preview.aclanthology.org/nschneid-patch-3/2021.iwpt-1.15.pdf