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--- |
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annotations_creators: [] |
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language_creators: [] |
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language: |
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- si |
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- en |
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license: |
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- mit |
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multilinguality: |
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- multilingual |
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size_categories: [] |
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source_datasets: [] |
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task_categories: |
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- text-classification |
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task_ids: |
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- sentiment-analysis |
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- hate-speech-detection |
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- humor-detection |
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- language-identification |
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- aspect-identification |
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--- |
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# Sinhala-English-Code-Mixed-Code-Switched-Dataset |
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This dataset contains 10,000 comments that have been annotated at the sentence level for sentiment analysis, humor detection, hate speech detection, aspect identification, and language identification. |
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The following is the tag scheme. |
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* Sentiment - Positive, Negative, Neutral, Conflict |
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* Humor - Humorous, Non humorous |
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* Hate Speech - Hate-Inducing, Abusive, Not offensive |
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* Aspect - Network, Billing or Price, Package, Customer Service, Data, Service or product, None |
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* Language ID - Sinhala, English, Sin-Eng, Eng-Sin, Mixed, Named-Entity, Symbol |
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If this datsaet is used, please give due credit by citing |
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Rathnayake, Himashi, et al. "Adapter-based fine-tuning of pre-trained multilingual language models for code-mixed and code-switched text classification." Knowledge and Information Systems 64.7 (2022): 1937-1966. |
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Other papers that use this dataset: |
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Rathnayake, Himashi, et al. "AdapterFusion-based multi-task learning for code-mixed and code-switched text classification." Engineering Applications of Artificial Intelligence 127 (2024): 107239. |
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Udawatta, Pasindu, et al. "Use of prompt-based learning for code-mixed and code-switched text classification." World Wide Web 27.5 (2024): 63. |
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