Abstract
In this paper, we propose efficient and less resource-intensive strategies for Konkani-English code-mixed social media text. which witnesses several challenges as compared to tagging general normal text. Part-of-Speech Tagging is a primary and an important step for many Natural Language Processing Applications. This paper reports work on annotating code-mixed Konkani-English data collected from social media site Facebook, which consists of more than four thousands posts from Facebook and developed automatic Part-of-Speech Taggers for this corpus. Part-of-Speech tagging is considered as a classification problem and we use different classifiers such as CRFs, SVM with different combinations of features.
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Phadte, A., Arsekar, R. (2018). Part-of-Speech Tagger for Konkani-English Code-Mixed Social Media Text. In: Silberztein, M., Atigui, F., Kornyshova, E., Métais, E., Meziane, F. (eds) Natural Language Processing and Information Systems. NLDB 2018. Lecture Notes in Computer Science(), vol 10859. Springer, Cham. https://doi.org/10.1007/978-3-319-91947-8_31
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DOI: https://doi.org/10.1007/978-3-319-91947-8_31
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