Abstract
This paper describes our system submission for the ACL 2018 shared task on named entity recognition (NER) in code-switched Twitter data. Our best result (F1 = 53.65) was obtained using a Support Vector Machine (SVM) with 14 features combined with rule-based post processing.- Anthology ID:
- W18-3218
- 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:
- 132–137
- Language:
- URL:
- https://aclanthology.org/W18-3218
- DOI:
- 10.18653/v1/W18-3218
- Cite (ACL):
- Daniel Claeser, Samantha Kent, and Dennis Felske. 2018. Multilingual Named Entity Recognition on Spanish-English Code-switched Tweets using Support Vector Machines. In Proceedings of the Third Workshop on Computational Approaches to Linguistic Code-Switching, pages 132–137, Melbourne, Australia. Association for Computational Linguistics.
- Cite (Informal):
- Multilingual Named Entity Recognition on Spanish-English Code-switched Tweets using Support Vector Machines (Claeser et al., ACL 2018)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/W18-3218.pdf