Abstract
We present the UTFPR system for the OffensEval shared task of SemEval 2019: A character-to-word-to-sentence compositional RNN model trained exclusively over the training data provided by the organizers. We find that, although not very competitive for the task at hand, it offers a robust solution to the orthographic irregularity inherent to tweets.- Anthology ID:
- S19-2140
- Volume:
- Proceedings of the 13th International Workshop on Semantic Evaluation
- Month:
- June
- Year:
- 2019
- Address:
- Minneapolis, Minnesota, USA
- Editors:
- Jonathan May, Ekaterina Shutova, Aurelie Herbelot, Xiaodan Zhu, Marianna Apidianaki, Saif M. Mohammad
- Venue:
- SemEval
- SIG:
- SIGLEX
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 801–805
- Language:
- URL:
- https://aclanthology.org/S19-2140
- DOI:
- 10.18653/v1/S19-2140
- Cite (ACL):
- Gustavo Henrique Paetzold. 2019. UTFPR at SemEval-2019 Task 6: Relying on Compositionality to Find Offense. In Proceedings of the 13th International Workshop on Semantic Evaluation, pages 801–805, Minneapolis, Minnesota, USA. Association for Computational Linguistics.
- Cite (Informal):
- UTFPR at SemEval-2019 Task 6: Relying on Compositionality to Find Offense (Paetzold, SemEval 2019)
- PDF:
- https://preview.aclanthology.org/proper-vol2-ingestion/S19-2140.pdf