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--- |
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license: cc-by-4.0 |
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task_categories: |
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- text-classification |
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- zero-shot-classification |
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language: |
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- en |
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tags: |
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- Human Values |
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- Value Detection |
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- Multi-Label |
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pretty_name: Human Value Detection Dataset |
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size_categories: |
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- 1K<n<10K |
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--- |
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Touché23-ValueEval |
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================== |
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[link](https://webis.de/data.html#touche23-valueeval) |
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Usage: |
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``` |
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from datasets import load_dataset |
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import ast |
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def convert_labels(example): |
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example["Labels"] = [i for i in ast.literal_eval(example["Labels"])] |
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return example |
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valueeval23 = load_dataset("webis/Touche23-ValueEval") |
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training_dataset = valueeval23["training"].map(convert_labels) |
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``` |
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See available dataset parts: |
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``` |
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valueeval23 |
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``` |
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The `Labels` for each example is an array of 1s (argument resorts to value) and 0s (argument does not resort to value). The order is the same as in the original files: |
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``` |
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labels = ["Self-direction: thought", "Self-direction: action", "Stimulation", "Hedonism", "Achievement", "Power: dominance", "Power: resources", "Face", "Security: personal", "Security: societal", "Tradition", "Conformity: rules", "Conformity: interpersonal", "Humility", "Benevolence: caring", "Benevolence: dependability", "Universalism: concern", "Universalism: nature", "Universalism: tolerance", "Universalism: objectivity"] |
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``` |
