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.
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.
Metadata
| 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 Institutes 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) |
| 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 INVALID USER. Last Modified 27 Apr 2023 14:02 |
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