INGEOTEC at SemEval-2020 Task 12: Multilingual Classification of Offensive Text
Sabino Miranda-Jiménez, Eric S. Tellez, Mario Graff, Daniela Moctezuma
Abstract
This paper describes our participation in OffensEval challenges for English, Arabic, Danish, Turkish, and Greek languages. We used several approaches, such as μTC, TextCategorization, and EvoMSA. Best results were achieved with EvoMSA, which is a multilingual and domain-independent architecture that combines the prediction from different knowledge sources to solve text classification problems.- Anthology ID:
- 2020.semeval-1.262
- Volume:
- Proceedings of the Fourteenth Workshop on Semantic Evaluation
- Month:
- December
- Year:
- 2020
- Address:
- Barcelona (online)
- Venue:
- SemEval
- SIGs:
- SIGLEX | SIGSEM
- Publisher:
- International Committee for Computational Linguistics
- Note:
- Pages:
- 1992–1997
- Language:
- URL:
- https://aclanthology.org/2020.semeval-1.262
- DOI:
- 10.18653/v1/2020.semeval-1.262
- Cite (ACL):
- Sabino Miranda-Jiménez, Eric S. Tellez, Mario Graff, and Daniela Moctezuma. 2020. INGEOTEC at SemEval-2020 Task 12: Multilingual Classification of Offensive Text. In Proceedings of the Fourteenth Workshop on Semantic Evaluation, pages 1992–1997, Barcelona (online). International Committee for Computational Linguistics.
- Cite (Informal):
- INGEOTEC at SemEval-2020 Task 12: Multilingual Classification of Offensive Text (Miranda-Jiménez et al., SemEval 2020)
- PDF:
- https://preview.aclanthology.org/ingestion-script-update/2020.semeval-1.262.pdf