Named Entity Recognition on Code-Switched Data Using Conditional Random Fields

Utpal Kumar Sikdar; Biswanath Barik; Björn Gambäck

doi:10.18653/v1/W18-3215

Named Entity Recognition on Code-Switched Data Using Conditional Random Fields

Utpal Kumar Sikdar, Biswanath Barik, Björn Gambäck

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Abstract

Named Entity Recognition is an important information extraction task that identifies proper names in unstructured texts and classifies them into some pre-defined categories. Identification of named entities in code-mixed social media texts is a more difficult and challenging task as the contexts are short, ambiguous and often noisy. This work proposes a Conditional Random Fields based named entity recognition system to identify proper names in code-switched data and classify them into nine categories. The system ranked fifth among nine participant systems and achieved a 59.25% F1-score.

Anthology ID:: W18-3215
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:: 115–119
Language:
URL:: https://aclanthology.org/W18-3215/
DOI:: 10.18653/v1/W18-3215
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Cite (ACL):: Utpal Kumar Sikdar, Biswanath Barik, and Björn Gambäck. 2018. Named Entity Recognition on Code-Switched Data Using Conditional Random Fields. In Proceedings of the Third Workshop on Computational Approaches to Linguistic Code-Switching, pages 115–119, Melbourne, Australia. Association for Computational Linguistics.
Cite (Informal):: Named Entity Recognition on Code-Switched Data Using Conditional Random Fields (Sikdar et al., ACL 2018)
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PDF:: https://aclanthology.org/W18-3215.pdf

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@inproceedings{sikdar-etal-2018-named,
    title = "Named Entity Recognition on Code-Switched Data Using Conditional Random Fields",
    author = {Sikdar, Utpal Kumar  and
      Barik, Biswanath  and
      Gamb{\"a}ck, Bj{\"o}rn},
    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/W18-3215/",
    doi = "10.18653/v1/W18-3215",
    pages = "115--119",
    abstract = "Named Entity Recognition is an important information extraction task that identifies proper names in unstructured texts and classifies them into some pre-defined categories. Identification of named entities in code-mixed social media texts is a more difficult and challenging task as the contexts are short, ambiguous and often noisy. This work proposes a Conditional Random Fields based named entity recognition system to identify proper names in code-switched data and classify them into nine categories. The system ranked fifth among nine participant systems and achieved a 59.25{\%} F1-score."
}

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%0 Conference Proceedings
%T Named Entity Recognition on Code-Switched Data Using Conditional Random Fields
%A Sikdar, Utpal Kumar
%A Barik, Biswanath
%A Gambäck, Björn
%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 sikdar-etal-2018-named
%X Named Entity Recognition is an important information extraction task that identifies proper names in unstructured texts and classifies them into some pre-defined categories. Identification of named entities in code-mixed social media texts is a more difficult and challenging task as the contexts are short, ambiguous and often noisy. This work proposes a Conditional Random Fields based named entity recognition system to identify proper names in code-switched data and classify them into nine categories. The system ranked fifth among nine participant systems and achieved a 59.25% F1-score.
%R 10.18653/v1/W18-3215
%U https://aclanthology.org/W18-3215/
%U https://doi.org/10.18653/v1/W18-3215
%P 115-119

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Markdown (Informal)

[Named Entity Recognition on Code-Switched Data Using Conditional Random Fields](https://aclanthology.org/W18-3215/) (Sikdar et al., ACL 2018)

Named Entity Recognition on Code-Switched Data Using Conditional Random Fields (Sikdar et al., ACL 2018)

ACL

Utpal Kumar Sikdar, Biswanath Barik, and Björn Gambäck. 2018. Named Entity Recognition on Code-Switched Data Using Conditional Random Fields. In Proceedings of the Third Workshop on Computational Approaches to Linguistic Code-Switching, pages 115–119, Melbourne, Australia. Association for Computational Linguistics.