Abstract
Our submission to the GEM data-to-text shared task aims to assess the quality of texts produced by the combination of a rule-based system with a language model of reduced size, by first using a rule-based generator to convert input triples into semantically correct English text, and then a language model to paraphrase these texts to make them more fluent. The texts are translated to languages other than English with the NLLB machine translation system.- Anthology ID:
- 2024.inlg-genchal.9
- 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:
- 84–91
- Language:
- URL:
- https://preview.aclanthology.org/add_missing_videos/2024.inlg-genchal.9/
- DOI:
- Cite (ACL):
- Simon Mille, Mohammed Sabry, and Anya Belz. 2024. DCU-NLG-Small at the GEM’24 Data-to-Text Task: Rule-based generation and post-processing with T5-Base. In Proceedings of the 17th International Natural Language Generation Conference: Generation Challenges, pages 84–91, Tokyo, Japan. Association for Computational Linguistics.
- Cite (Informal):
- DCU-NLG-Small at the GEM’24 Data-to-Text Task: Rule-based generation and post-processing with T5-Base (Mille et al., INLG 2024)
- PDF:
- https://preview.aclanthology.org/add_missing_videos/2024.inlg-genchal.9.pdf