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@@ -4,4 +4,10 @@ task_categories:
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  - question-answering
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  language:
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  - de
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- ---
 
 
 
 
 
 
 
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  - question-answering
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  language:
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  - de
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+ ---
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+
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+ This is the dataset from GiCCS: A German in-Context Conversational Similarity Benchmark paper:
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+ https://aclanthology.org/2022.gem-1.30/
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+ Please cite the following paper:
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+ Shima Asaadi, Zahra Kolagar, Alina Liebel, and Alessandra Zarcone. 2022. GiCCS: A German in-Context Conversational Similarity Benchmark. In Proceedings of the 2nd Workshop on Natural Language Generation, Evaluation, and Metrics (GEM), pages 351–362, Abu Dhabi, United Arab Emirates (Hybrid). Association for Computational Linguistics.