The UPC RDF-to-Text System at WebNLG Challenge 2020

David Bergés, Roser Cantenys, Roger Creus, Oriol Domingo, José A. R. Fonollosa


Abstract
This work describes the end-to-end system architecture presented at WebNLG Challenge 2020. The system follows the traditional Machine Translation (MT) pipeline, based on the Transformer model, applied in most text-totext problems. Our solution is enriched by means of a Back Translation step over the original corpus. Thus, the system directly relies on lexicalise format since the synthetic data limits the use of delexicalisation.
Anthology ID:
2020.webnlg-1.19
Volume:
Proceedings of the 3rd International Workshop on Natural Language Generation from the Semantic Web (WebNLG+)
Month:
12
Year:
2020
Address:
Dublin, Ireland (Virtual)
Editors:
Thiago Castro Ferreira, Claire Gardent, Nikolai Ilinykh, Chris van der Lee, Simon Mille, Diego Moussallem, Anastasia Shimorina
Venue:
WebNLG
SIG:
SIGGEN
Publisher:
Association for Computational Linguistics
Note:
Pages:
167–170
Language:
URL:
https://aclanthology.org/2020.webnlg-1.19
DOI:
Bibkey:
Cite (ACL):
David Bergés, Roser Cantenys, Roger Creus, Oriol Domingo, and José A. R. Fonollosa. 2020. The UPC RDF-to-Text System at WebNLG Challenge 2020. In Proceedings of the 3rd International Workshop on Natural Language Generation from the Semantic Web (WebNLG+), pages 167–170, Dublin, Ireland (Virtual). Association for Computational Linguistics.
Cite (Informal):
The UPC RDF-to-Text System at WebNLG Challenge 2020 (Bergés et al., WebNLG 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.webnlg-1.19.pdf