Multilingual Named Entity Recognition on Spanish-English Code-switched Tweets using Support Vector Machines

Daniel Claeser, Samantha Kent, Dennis Felske


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
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
Bibkey:
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)
Copy Citation:
PDF:
https://preview.aclanthology.org/ingestion-script-update/W18-3218.pdf