@inproceedings{trivedi-etal-2018-iit,
title = "{IIT} ({BHU}) Submission for the {ACL} Shared Task on Named Entity Recognition on Code-switched Data",
author = "Trivedi, Shashwat and
Rangwani, Harsh and
Kumar Singh, Anil",
editor = "Aguilar, Gustavo and
AlGhamdi, Fahad and
Soto, Victor and
Solorio, Thamar and
Diab, Mona and
Hirschberg, Julia",
booktitle = "Proceedings of the Third Workshop on Computational Approaches to Linguistic Code-Switching",
month = jul,
year = "2018",
address = "Melbourne, Australia",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W18-3220",
doi = "10.18653/v1/W18-3220",
pages = "148--153",
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{\%}.",
}
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<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%.</abstract>
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%0 Conference Proceedings
%T IIT (BHU) Submission for the ACL Shared Task on Named Entity Recognition on Code-switched Data
%A Trivedi, Shashwat
%A Rangwani, Harsh
%A Kumar Singh, Anil
%Y Aguilar, Gustavo
%Y AlGhamdi, Fahad
%Y Soto, Victor
%Y Solorio, Thamar
%Y Diab, Mona
%Y Hirschberg, Julia
%S Proceedings of the Third Workshop on Computational Approaches to Linguistic Code-Switching
%D 2018
%8 July
%I Association for Computational Linguistics
%C Melbourne, Australia
%F trivedi-etal-2018-iit
%X 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%.
%R 10.18653/v1/W18-3220
%U https://aclanthology.org/W18-3220
%U https://doi.org/10.18653/v1/W18-3220
%P 148-153
Markdown (Informal)
[IIT (BHU) Submission for the ACL Shared Task on Named Entity Recognition on Code-switched Data](https://aclanthology.org/W18-3220) (Trivedi et al., ACL 2018)
ACL