Abstract
The MultiCoNER II shared task aims at detecting complex, ambiguous named entities with fine-grained types in a low context setting. Previous winning systems incorporated external knowledge bases to retrieve helpful contexts. In our submission we additionally propose splitting the NER task into two stages, a Span Extraction Step, and an Entity Classification step. Our results show that the former does not suffer from the low context setting comparably, and in so leading to a higher overall performance for an external KB-assisted system. We achieve 3rd place on the multilingual track and an average of 6th place overall.- Anthology ID:
- 2023.semeval-1.159
- Volume:
- Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)
- Month:
- July
- Year:
- 2023
- Address:
- Toronto, Canada
- Editors:
- Atul Kr. Ojha, A. Seza Doğruöz, Giovanni Da San Martino, Harish Tayyar Madabushi, Ritesh Kumar, Elisa Sartori
- Venue:
- SemEval
- SIG:
- SIGLEX
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 1148–1153
- Language:
- URL:
- https://preview.aclanthology.org/build-pipeline-with-new-library/2023.semeval-1.159/
- DOI:
- 10.18653/v1/2023.semeval-1.159
- Cite (ACL):
- Mohab Elkaref, Nathan Herr, Shinnosuke Tanaka, and Geeth De Mel. 2023. NLPeople at SemEval-2023 Task 2: A Staged Approach for Multilingual Named Entity Recognition. In Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023), pages 1148–1153, Toronto, Canada. Association for Computational Linguistics.
- Cite (Informal):
- NLPeople at SemEval-2023 Task 2: A Staged Approach for Multilingual Named Entity Recognition (Elkaref et al., SemEval 2023)
- PDF:
- https://preview.aclanthology.org/build-pipeline-with-new-library/2023.semeval-1.159.pdf