Abstract
This paper presents our system entitled ‘LIIR’ for SemEval-2020 Task 12 on Multilingual Offensive Language Identification in Social Media (OffensEval 2). We have participated in sub-task A for English, Danish, Greek, Arabic, and Turkish languages. We adapt and fine-tune the BERT and Multilingual Bert models made available by Google AI for English and non-English languages respectively. For the English language, we use a combination of two fine-tuned BERT models. For other languages we propose a cross-lingual augmentation approach in order to enrich training data and we use Multilingual BERT to obtain sentence representations.- Anthology ID:
- 2020.semeval-1.274
- Volume:
- Proceedings of the Fourteenth Workshop on Semantic Evaluation
- Month:
- December
- Year:
- 2020
- Address:
- Barcelona (online)
- Venue:
- SemEval
- SIG:
- SIGLEX
- Publisher:
- International Committee for Computational Linguistics
- Note:
- Pages:
- 2073–2079
- Language:
- URL:
- https://aclanthology.org/2020.semeval-1.274
- DOI:
- 10.18653/v1/2020.semeval-1.274
- Cite (ACL):
- Erfan Ghadery and Marie-Francine Moens. 2020. LIIR at SemEval-2020 Task 12: A Cross-Lingual Augmentation Approach for Multilingual Offensive Language Identification. In Proceedings of the Fourteenth Workshop on Semantic Evaluation, pages 2073–2079, Barcelona (online). International Committee for Computational Linguistics.
- Cite (Informal):
- LIIR at SemEval-2020 Task 12: A Cross-Lingual Augmentation Approach for Multilingual Offensive Language Identification (Ghadery & Moens, SemEval 2020)
- PDF:
- https://preview.aclanthology.org/remove-xml-comments/2020.semeval-1.274.pdf
- Data
- OLID