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

Daniel Claeser, Samantha Kent, Dennis Felske

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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
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/teach-a-man-to-fish/W18-3218.pdf