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Creation of Corpus and Analysis in Code-Mixed Kannada-English Social Media Data for POS Tagging

2020-12-01 · ICON 2020 12 · Abhinav Reddy Appidi, Vamshi Krishna Srirangam, Darsi Suhas, Manish Shrivastava

Part-of-Speech (POS) is one of the essential tasks for many Natural Language Processing (NLP) applications. There has been a significant amount of work done in POS tagging for resource-rich languages. POS tagging is an essential phase of text analysis in understanding the semantics and context of language. These tags are useful for higher-level tasks such as building parse trees, which can be used for Named Entity Recognition, Coreference resolution, Sentiment Analysis, and Question Answering. There has been work done on code-mixed social media corpus but not on POS tagging of Kannada-English code-mixed data. Here, we present Kannada-English code- mixed social media corpus annotated with corresponding POS tags. We also experimented with machine learning classification models CRF, Bi-LSTM, and Bi-LSTM-CRF models on our corpus.

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coreference-resolutionCoreference Resolutionnamed-entity-recognitionNamed Entity RecognitionNamed Entity Recognition (NER)POSPOS TaggingQuestion AnsweringSentiment Analysis

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