Abstract
We hereby present our submission to the Shared Task in Evaluating Accuracy at the INLG 2021 Conference. Our evaluation protocol relies on three main components; rules and text classifiers that pre-annotate the dataset, a human annotator that validates the pre-annotations, and a web interface that facilitates this validation. Our submission consists in fact of two submissions; we first analyze solely the performance of the rules and classifiers (pre-annotations), and then the human evaluation aided by the former pre-annotations using the web interface (hybrid). The code for the web interface and the classifiers is publicly available.- Anthology ID:
- 2021.inlg-1.26
- Volume:
- Proceedings of the 14th International Conference on Natural Language Generation
- Month:
- August
- Year:
- 2021
- Address:
- Aberdeen, Scotland, UK
- Venue:
- INLG
- SIG:
- SIGGEN
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 266–270
- Language:
- URL:
- https://aclanthology.org/2021.inlg-1.26
- DOI:
- Cite (ACL):
- Nicolas Garneau and Luc Lamontagne. 2021. Shared Task in Evaluating Accuracy: Leveraging Pre-Annotations in the Validation Process. In Proceedings of the 14th International Conference on Natural Language Generation, pages 266–270, Aberdeen, Scotland, UK. Association for Computational Linguistics.
- Cite (Informal):
- Shared Task in Evaluating Accuracy: Leveraging Pre-Annotations in the Validation Process (Garneau & Lamontagne, INLG 2021)
- PDF:
- https://preview.aclanthology.org/starsem-semeval-split/2021.inlg-1.26.pdf