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  ### Dataset Summary
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- SemRel2024 is a collection of Semantic Textual Relatedness (STR) datasets for 14 languages, including African and Asian languages. The dataset is designed for the SemEval-2024 Task 1: Semantic Textual Relatedness for African and Asian Languages. The task aims to evaluate the ability of systems to measure the semantic relatedness between two text segments, such as sentences or phrases.
 
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- ### Supported Tasks and Leaderboards
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- The SemRel2024 dataset can be used for the Semantic Textual Relatedness task, which involves predicting the degree of semantic relatedness between two text segments on a scale, typically from 0 (not related at all) to 5 (highly related).
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- [SemEval-2024 Task 1: Semantic Textual Relatedness for African and Asian Languages](https://github.com/semantic-textual-relatedness/Semantic_Relatedness_SemEval2024)
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  ### Languages
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  ### Dataset Summary
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+ SemRel2024 is a collection of Semantic Textual Relatedness (STR) datasets for 14 languages, including African and Asian languages. The datasets are composed of sentence pairs, each assigned a relatedness score between 0 (completely) unrelated and 1 (maximally related) with a large range of expected relatedness values.
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+ SemRel2024 dataset was used as part of the SemEval2024 shared task 1. The task aims to evaluate the ability of systems to measure the semantic relatedness between two sentences.
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  ### Languages
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