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  ## Dataset Summary
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  The present dataset is a result of processing the [IBM Debater Claim Stance Dataset](https://huggingface.co/datasets/ibm/claim_stance) to create representative samples. The size has been reduced to roughly 100 entries, enabling the benchmarking of models for relation-based argument mining tasks with limited resources.
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- You can also find here the associated benchmarking [framework](https://github.com/coding-kelps/liaisons-experiments) and [results](https://huggingface.co/coding-kelps/liaispns-experiments-results).
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  The sample also modifies the original dataset to achieve a more balanced plurality of stances and topics, and creates a new "unrelated" class in argument relation (following a simple rule-based data augmentation algorithm). Further details on the preprocessing can be found on [GitHub](https://github.com/coding-kelps/liaisons-preprocess).
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  ## Dataset Summary
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  The present dataset is a result of processing the [IBM Debater Claim Stance Dataset](https://huggingface.co/datasets/ibm/claim_stance) to create representative samples. The size has been reduced to roughly 100 entries, enabling the benchmarking of models for relation-based argument mining tasks with limited resources.
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+ You can also find here the associated benchmarking [framework](https://github.com/coding-kelps/liaisons-experiments) and [results](https://huggingface.co/datasets/coding-kelps/liaisons-experiments-results).
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  The sample also modifies the original dataset to achieve a more balanced plurality of stances and topics, and creates a new "unrelated" class in argument relation (following a simple rule-based data augmentation algorithm). Further details on the preprocessing can be found on [GitHub](https://github.com/coding-kelps/liaisons-preprocess).
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