Datasets:
Update README.md
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README.md
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---
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license: apache-2.0
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---
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license: apache-2.0
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task_categories:
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- question-answering
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language:
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- en
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pretty_name: CopyColors MCQA
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size_categories:
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- n<1K
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configs:
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- config_name: 2_answer_choices
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data_files:
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- split: train
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path: 2_answer_choices/train.jsonl
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- split: validation
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path: 2_answer_choices/validation.jsonl
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- split: test
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path: 2_answer_choices/test.jsonl
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- config_name: 3_answer_choices
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data_files:
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- split: train
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path: 3_answer_choices/train.jsonl
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- split: validation
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path: 3_answer_choices/validation.jsonl
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- split: test
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path: 3_answer_choices/test.jsonl
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- config_name: 4_answer_choices
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data_files:
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- split: train
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path: 4_answer_choices/train.jsonl
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- split: validation
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path: 4_answer_choices/validation.jsonl
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- split: test
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path: 4_answer_choices/test.jsonl
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- config_name: 5_answer_choices
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data_files:
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- split: train
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path: 5_answer_choices/train.jsonl
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- split: validation
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path: 5_answer_choices/validation.jsonl
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- split: test
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path: 5_answer_choices/test.jsonl
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- config_name: 6_answer_choices
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data_files:
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- split: train
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path: 6_answer_choices/train.jsonl
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- split: validation
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path: 6_answer_choices/validation.jsonl
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- split: test
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path: 6_answer_choices/test.jsonl
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- config_name: 7_answer_choices
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data_files:
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- split: train
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path: 7_answer_choices/train.jsonl
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- split: validation
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path: 7_answer_choices/validation.jsonl
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- split: test
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path: 7_answer_choices/test.jsonl
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- config_name: 8_answer_choices
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data_files:
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- split: train
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path: 8_answer_choices/train.jsonl
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- split: validation
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path: 8_answer_choices/validation.jsonl
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- split: test
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path: 8_answer_choices/test.jsonl
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- config_name: 9_answer_choices
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data_files:
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- split: train
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path: 9_answer_choices/train.jsonl
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- split: validation
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path: 9_answer_choices/validation.jsonl
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- split: test
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path: 9_answer_choices/test.jsonl
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- config_name: 10_answer_choices
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data_files:
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- split: train
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path: 10_answer_choices/train.jsonl
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- split: validation
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path: 10_answer_choices/validation.jsonl
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- split: test
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path: 10_answer_choices/test.jsonl
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---
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This dataset consists of formatted n-way multiple choice questions, where n is in [2,10]. The task itself is simply to copy the prototypical color from the context and produce the corresponding color's answer choice letter.
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The "prototypical colors" dataset instances themselves come from [Memory Colors](https://aclanthology.org/2021.blackboxnlp-1.10/) (Norland et al. 2021) and [corypaik/coda](https://huggingface.co/datasets/corypaik/coda) (instances whose object_group is 0, indicating participants agreed on a prototypical color of that object).
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