Abstract
This paper describes the best performing system for the shared task on Named Entity Recognition (NER) on code-switched data for the language pair Spanish-English (ENG-SPA). We introduce a gated neural architecture for the NER task. Our final model achieves an F1 score of 63.76%, outperforming the baseline by 10%.- Anthology ID:
- W18-3220
- Volume:
- Proceedings of the Third Workshop on Computational Approaches to Linguistic Code-Switching
- Month:
- July
- Year:
- 2018
- Address:
- Melbourne, Australia
- Editors:
- Gustavo Aguilar, Fahad AlGhamdi, Victor Soto, Thamar Solorio, Mona Diab, Julia Hirschberg
- Venue:
- ACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 148–153
- Language:
- URL:
- https://aclanthology.org/W18-3220
- DOI:
- 10.18653/v1/W18-3220
- Cite (ACL):
- Shashwat Trivedi, Harsh Rangwani, and Anil Kumar Singh. 2018. IIT (BHU) Submission for the ACL Shared Task on Named Entity Recognition on Code-switched Data. In Proceedings of the Third Workshop on Computational Approaches to Linguistic Code-Switching, pages 148–153, Melbourne, Australia. Association for Computational Linguistics.
- Cite (Informal):
- IIT (BHU) Submission for the ACL Shared Task on Named Entity Recognition on Code-switched Data (Trivedi et al., ACL 2018)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-1/W18-3220.pdf