NamedEntityRangers at SemEval-2022 Task 11: Transformer-based Approaches for Multilingual Complex Named Entity Recognition
Amina Miftahova, Alexander Pugachev, Artem Skiba, Katya Artemova, Tatiana Batura, Pavel Braslavski, Vladimir Ivanov
Abstract
This paper presents the two submissions of NamedEntityRangers Team to the MultiCoNER Shared Task, hosted at SemEval-2022. We evaluate two state-of-the-art approaches, of which both utilize pre-trained multi-lingual language models differently. The first approach follows the token classification schema, in which each token is assigned with a tag. The second approach follows a recent template-free paradigm, in which an encoder-decoder model translates the input sequence of words to a special output, encoding named entities with predefined labels. We utilize RemBERT and mT5 as backbone models for these two approaches, respectively. Our results show that the oldie but goodie token classification outperforms the template-free method by a wide margin. Our code is available at: https://github.com/Abiks/MultiCoNER.- Anthology ID:
- 2022.semeval-1.216
- Volume:
- Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)
- Month:
- July
- Year:
- 2022
- Address:
- Seattle, United States
- Venue:
- SemEval
- SIGs:
- SIGLEX | SIGSEM
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 1570–1575
- Language:
- URL:
- https://aclanthology.org/2022.semeval-1.216
- DOI:
- 10.18653/v1/2022.semeval-1.216
- Cite (ACL):
- Amina Miftahova, Alexander Pugachev, Artem Skiba, Katya Artemova, Tatiana Batura, Pavel Braslavski, and Vladimir Ivanov. 2022. NamedEntityRangers at SemEval-2022 Task 11: Transformer-based Approaches for Multilingual Complex Named Entity Recognition. In Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022), pages 1570–1575, Seattle, United States. Association for Computational Linguistics.
- Cite (Informal):
- NamedEntityRangers at SemEval-2022 Task 11: Transformer-based Approaches for Multilingual Complex Named Entity Recognition (Miftahova et al., SemEval 2022)
- PDF:
- https://preview.aclanthology.org/ingestion-script-update/2022.semeval-1.216.pdf
- Code
- abiks/multiconer
- Data
- MultiCoNER