Abstract
This work presents a two-stage approach for tackling low-resource AMR-to-text generation for Brazilian Portuguese. Our approach consists of (1) generating a masked surface realization in which some tokens are masked according to its Part-of-Speech class and (2) infilling the masked tokens according to the AMR graph and the previous masked surface realization. Results show a slight improvement over the baseline, mainly in BLEU (1.63) and METEOR (0.02) scores. Moreover, we evaluate the pipeline components separately, showing that the bottleneck of the pipeline is the masked surface realization. Finally, the human evaluation suggests that models still suffer from hallucinations, and some strategies to deal with the problems found are proposed.- Anthology ID:
- 2022.gem-1.49
- Volume:
- Proceedings of the 2nd Workshop on Natural Language Generation, Evaluation, and Metrics (GEM)
- Month:
- December
- Year:
- 2022
- Address:
- Abu Dhabi, United Arab Emirates (Hybrid)
- Editors:
- Antoine Bosselut, Khyathi Chandu, Kaustubh Dhole, Varun Gangal, Sebastian Gehrmann, Yacine Jernite, Jekaterina Novikova, Laura Perez-Beltrachini
- Venue:
- GEM
- SIG:
- SIGGEN
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 531–538
- Language:
- URL:
- https://preview.aclanthology.org/add_missing_videos/2022.gem-1.49/
- DOI:
- 10.18653/v1/2022.gem-1.49
- Cite (ACL):
- Marco Antonio Sobrevilla Cabezudo and Thiago Pardo. 2022. Exploring a POS-based Two-stage Approach for Improving Low-Resource AMR-to-Text Generation. In Proceedings of the 2nd Workshop on Natural Language Generation, Evaluation, and Metrics (GEM), pages 531–538, Abu Dhabi, United Arab Emirates (Hybrid). Association for Computational Linguistics.
- Cite (Informal):
- Exploring a POS-based Two-stage Approach for Improving Low-Resource AMR-to-Text Generation (Sobrevilla Cabezudo & Pardo, GEM 2022)
- PDF:
- https://preview.aclanthology.org/add_missing_videos/2022.gem-1.49.pdf