pyrealb at the GEM’24 Data-to-text Task: Symbolic English Text Generation from RDF Triples

Guy Lapalme


Abstract
We present a symbolic system, written in Python, used to participate in the English Data-to-text generation task of the GEM Shared Task at the Generation Challenges (INLG’24). The system runs quickly on a standard laptop, making it fast and predictable. It is also quite easy to adapt to a new domain.
Anthology ID:
2024.inlg-genchal.5
Volume:
Proceedings of the 17th International Natural Language Generation Conference: Generation Challenges
Month:
September
Year:
2024
Address:
Tokyo, Japan
Editors:
Simon Mille, Miruna-Adriana Clinciu
Venue:
INLG
SIG:
SIGGEN
Publisher:
Association for Computational Linguistics
Note:
Pages:
54–58
Language:
URL:
https://aclanthology.org/2024.inlg-genchal.5
DOI:
Bibkey:
Cite (ACL):
Guy Lapalme. 2024. pyrealb at the GEM’24 Data-to-text Task: Symbolic English Text Generation from RDF Triples. In Proceedings of the 17th International Natural Language Generation Conference: Generation Challenges, pages 54–58, Tokyo, Japan. Association for Computational Linguistics.
Cite (Informal):
pyrealb at the GEM’24 Data-to-text Task: Symbolic English Text Generation from RDF Triples (Lapalme, INLG 2024)
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PDF:
https://aclanthology.org/2024.inlg-genchal.5.pdf