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:
- 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)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/2020.webnlg-1.19.pdf