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://preview.aclanthology.org/add_missing_videos/2024.inlg-genchal.5/
- DOI:
- 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)
- PDF:
- https://preview.aclanthology.org/add_missing_videos/2024.inlg-genchal.5.pdf