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Part-of-speech tagging of code-mixed social media content: pipeline, stacking and joint modelling

Barman, Utsab, Wagner, Joachim ORCID: 0000-0002-8290-3849 and Foster, Jennifer ORCID: 0000-0002-7789-4853 (2016) Part-of-speech tagging of code-mixed social media content: pipeline, stacking and joint modelling. In: Second Workshop on Computational Approaches to Code Switching, 2 Nov 2016, Austin, Texas, USA.

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Abstract

Multilingual users of social media sometimes use multiple languages during conversation. Mixing multiple languages in content is known as code-mixing. We annotate a subset of a trilingual code-mixed corpus (Barman et al., 2014) with part-of-speech (POS) tags. We investigate two state-of-the-art POS tagging techniques for code-mixed content and combine the features of the two systems to build a better POS tagger. Furthermore, we investigate the use of a joint model which performs language identification (LID) and partof-speech (POS) tagging simultaneously.

Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Subjects:Computer Science > Machine translating
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Research Initiatives and Centres > ADAPT
Published in: Proceedings of the Second Workshop on Computational Approaches to Code Switching. . Association for Computational Linguistics (ACL).
Publisher:Association for Computational Linguistics (ACL)
Official URL:https://doi.org/10.18653/v1/W16-5804
Copyright Information:© 2016 Association for Computational Linguistics (ACL) CC- BY- 4.0
Funders:Science Foundation Ireland (Grant 12/CE/I2267) as part of CNGL (www.cngl.ie) at Dublin City University.
ID Code:23067
Deposited On:11 Mar 2019 11:56 by Thomas Murtagh . Last Modified 27 Aug 2020 14:15

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