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--- |
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license: cc-by-nc-sa-4.0 |
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task_categories: |
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- multiple-choice |
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- text-generation |
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language: |
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- ar |
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tags: |
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- cultural |
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- commonsense |
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- commonsense cultural knowledge |
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pretty_name: ArabCulture |
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size_categories: |
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- 1K<n<10K |
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dataset_info: |
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- config_name: Algeria |
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features: |
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- name: worker_id |
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dtype: string |
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- name: sample_id |
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dtype: string |
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- name: sub_topic |
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dtype: string |
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- name: first_statement |
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dtype: string |
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- name: options |
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struct: |
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- name: arabic_keys |
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sequence: string |
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- name: english_keys |
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sequence: string |
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- name: text |
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sequence: string |
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- name: answer_key |
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struct: |
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- name: arabic_answer_key |
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dtype: string |
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- name: english_answer_key |
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dtype: string |
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- name: relevant_to_this_country |
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dtype: string |
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- name: relevant_to_other_countries |
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dtype: string |
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- name: should_discard |
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dtype: string |
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- name: country |
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dtype: string |
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- name: region |
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dtype: string |
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splits: |
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- name: test |
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num_bytes: 138521 |
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num_examples: 271 |
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download_size: 54282 |
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dataset_size: 138521 |
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- config_name: Egypt |
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features: |
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- name: worker_id |
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dtype: string |
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- name: sample_id |
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dtype: string |
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- name: sub_topic |
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dtype: string |
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- name: first_statement |
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dtype: string |
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- name: options |
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struct: |
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- name: arabic_keys |
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sequence: string |
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- name: english_keys |
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sequence: string |
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- name: text |
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sequence: string |
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- name: answer_key |
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struct: |
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- name: arabic_answer_key |
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dtype: string |
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- name: english_answer_key |
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|
dtype: string |
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|
- name: relevant_to_this_country |
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|
dtype: string |
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- name: relevant_to_other_countries |
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|
dtype: string |
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- name: should_discard |
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dtype: string |
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- name: country |
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dtype: string |
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- name: region |
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dtype: string |
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splits: |
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- name: test |
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num_bytes: 133067 |
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num_examples: 265 |
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download_size: 48436 |
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dataset_size: 133067 |
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- config_name: Jordan |
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features: |
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- name: worker_id |
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dtype: string |
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- name: sample_id |
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dtype: string |
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|
- name: sub_topic |
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dtype: string |
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- name: first_statement |
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dtype: string |
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- name: options |
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struct: |
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- name: arabic_keys |
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sequence: string |
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- name: english_keys |
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sequence: string |
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- name: text |
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sequence: string |
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- name: answer_key |
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struct: |
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|
- name: arabic_answer_key |
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|
dtype: string |
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|
- name: english_answer_key |
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|
dtype: string |
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|
- name: relevant_to_this_country |
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|
dtype: string |
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|
- name: relevant_to_other_countries |
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|
dtype: string |
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|
- name: should_discard |
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|
dtype: string |
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|
- name: country |
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dtype: string |
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- name: region |
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dtype: string |
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splits: |
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- name: test |
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num_bytes: 151700 |
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num_examples: 290 |
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download_size: 53190 |
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dataset_size: 151700 |
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- config_name: KSA |
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features: |
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- name: worker_id |
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dtype: string |
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- name: sample_id |
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|
dtype: string |
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|
- name: sub_topic |
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|
dtype: string |
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- name: first_statement |
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|
dtype: string |
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- name: options |
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struct: |
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- name: arabic_keys |
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sequence: string |
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- name: english_keys |
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sequence: string |
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|
- name: text |
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sequence: string |
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- name: answer_key |
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struct: |
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|
- name: arabic_answer_key |
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|
dtype: string |
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|
- name: english_answer_key |
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|
dtype: string |
|
|
- name: relevant_to_this_country |
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|
dtype: string |
|
|
- name: relevant_to_other_countries |
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|
dtype: string |
|
|
- name: should_discard |
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|
dtype: string |
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|
- name: country |
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|
dtype: string |
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|
- name: region |
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|
dtype: string |
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splits: |
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|
- name: test |
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num_bytes: 131864 |
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num_examples: 261 |
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download_size: 49944 |
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dataset_size: 131864 |
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- config_name: Lebanon |
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|
features: |
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- name: worker_id |
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|
dtype: string |
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|
- name: sample_id |
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|
dtype: string |
|
|
- name: sub_topic |
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|
dtype: string |
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- name: first_statement |
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|
dtype: string |
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- name: options |
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struct: |
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|
- name: arabic_keys |
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sequence: string |
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- name: english_keys |
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sequence: string |
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|
- name: text |
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sequence: string |
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- name: answer_key |
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|
struct: |
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|
- name: arabic_answer_key |
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|
dtype: string |
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|
- name: english_answer_key |
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|
dtype: string |
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|
- name: relevant_to_this_country |
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|
dtype: string |
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|
- name: relevant_to_other_countries |
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|
dtype: string |
|
|
- name: should_discard |
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|
dtype: string |
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|
- name: country |
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|
dtype: string |
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|
- name: region |
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dtype: string |
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|
splits: |
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|
- name: test |
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num_bytes: 122498 |
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num_examples: 255 |
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download_size: 49462 |
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dataset_size: 122498 |
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- config_name: Libya |
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|
features: |
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|
- name: worker_id |
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dtype: string |
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|
- name: sample_id |
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|
dtype: string |
|
|
- name: sub_topic |
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|
dtype: string |
|
|
- name: first_statement |
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|
dtype: string |
|
|
- name: options |
|
|
struct: |
|
|
- name: arabic_keys |
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|
sequence: string |
|
|
- name: english_keys |
|
|
sequence: string |
|
|
- name: text |
|
|
sequence: string |
|
|
- name: answer_key |
|
|
struct: |
|
|
- name: arabic_answer_key |
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|
dtype: string |
|
|
- name: english_answer_key |
|
|
dtype: string |
|
|
- name: relevant_to_this_country |
|
|
dtype: string |
|
|
- name: relevant_to_other_countries |
|
|
dtype: string |
|
|
- name: should_discard |
|
|
dtype: string |
|
|
- name: country |
|
|
dtype: string |
|
|
- name: region |
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|
dtype: string |
|
|
splits: |
|
|
- name: test |
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|
num_bytes: 141730 |
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|
num_examples: 239 |
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download_size: 57006 |
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dataset_size: 141730 |
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|
- config_name: Morocco |
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|
features: |
|
|
- name: worker_id |
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|
dtype: string |
|
|
- name: sample_id |
|
|
dtype: string |
|
|
- name: sub_topic |
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|
dtype: string |
|
|
- name: first_statement |
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|
dtype: string |
|
|
- name: options |
|
|
struct: |
|
|
- name: arabic_keys |
|
|
sequence: string |
|
|
- name: english_keys |
|
|
sequence: string |
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|
- name: text |
|
|
sequence: string |
|
|
- name: answer_key |
|
|
struct: |
|
|
- name: arabic_answer_key |
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|
dtype: string |
|
|
- name: english_answer_key |
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|
dtype: string |
|
|
- name: relevant_to_this_country |
|
|
dtype: string |
|
|
- name: relevant_to_other_countries |
|
|
dtype: string |
|
|
- name: should_discard |
|
|
dtype: string |
|
|
- name: country |
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|
dtype: string |
|
|
- name: region |
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|
dtype: string |
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|
splits: |
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|
- name: test |
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num_bytes: 132122 |
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num_examples: 276 |
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download_size: 51299 |
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dataset_size: 132122 |
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- config_name: Palestine |
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features: |
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- name: worker_id |
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|
dtype: string |
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|
- name: sample_id |
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|
dtype: string |
|
|
- name: sub_topic |
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|
dtype: string |
|
|
- name: first_statement |
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|
dtype: string |
|
|
- name: options |
|
|
struct: |
|
|
- name: arabic_keys |
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|
sequence: string |
|
|
- name: english_keys |
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|
sequence: string |
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|
- name: text |
|
|
sequence: string |
|
|
- name: answer_key |
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|
struct: |
|
|
- name: arabic_answer_key |
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|
dtype: string |
|
|
- name: english_answer_key |
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|
dtype: string |
|
|
- name: relevant_to_this_country |
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|
dtype: string |
|
|
- name: relevant_to_other_countries |
|
|
dtype: string |
|
|
- name: should_discard |
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|
dtype: string |
|
|
- name: country |
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|
dtype: string |
|
|
- name: region |
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|
dtype: string |
|
|
splits: |
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|
- name: test |
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|
num_bytes: 137975 |
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num_examples: 273 |
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download_size: 49556 |
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dataset_size: 137975 |
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- config_name: Sudan |
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|
features: |
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|
- name: worker_id |
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|
dtype: string |
|
|
- name: sample_id |
|
|
dtype: string |
|
|
- name: sub_topic |
|
|
dtype: string |
|
|
- name: first_statement |
|
|
dtype: string |
|
|
- name: options |
|
|
struct: |
|
|
- name: arabic_keys |
|
|
sequence: string |
|
|
- name: english_keys |
|
|
sequence: string |
|
|
- name: text |
|
|
sequence: string |
|
|
- name: answer_key |
|
|
struct: |
|
|
- name: arabic_answer_key |
|
|
dtype: string |
|
|
- name: english_answer_key |
|
|
dtype: string |
|
|
- name: relevant_to_this_country |
|
|
dtype: string |
|
|
- name: relevant_to_other_countries |
|
|
dtype: string |
|
|
- name: should_discard |
|
|
dtype: string |
|
|
- name: country |
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|
dtype: string |
|
|
- name: region |
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|
dtype: string |
|
|
splits: |
|
|
- name: test |
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|
num_bytes: 145257 |
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|
num_examples: 256 |
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|
download_size: 53385 |
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dataset_size: 145257 |
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- config_name: Syria |
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|
features: |
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|
- name: worker_id |
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|
dtype: string |
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|
- name: sample_id |
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|
dtype: string |
|
|
- name: sub_topic |
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|
dtype: string |
|
|
- name: first_statement |
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|
dtype: string |
|
|
- name: options |
|
|
struct: |
|
|
- name: arabic_keys |
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|
sequence: string |
|
|
- name: english_keys |
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|
sequence: string |
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|
- name: text |
|
|
sequence: string |
|
|
- name: answer_key |
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|
struct: |
|
|
- name: arabic_answer_key |
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|
dtype: string |
|
|
- name: english_answer_key |
|
|
dtype: string |
|
|
- name: relevant_to_this_country |
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|
dtype: string |
|
|
- name: relevant_to_other_countries |
|
|
dtype: string |
|
|
- name: should_discard |
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|
dtype: string |
|
|
- name: country |
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|
dtype: string |
|
|
- name: region |
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|
dtype: string |
|
|
splits: |
|
|
- name: test |
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|
num_bytes: 120795 |
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num_examples: 279 |
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download_size: 44754 |
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dataset_size: 120795 |
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- config_name: Tunisia |
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features: |
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|
- name: worker_id |
|
|
dtype: string |
|
|
- name: sample_id |
|
|
dtype: string |
|
|
- name: sub_topic |
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|
dtype: string |
|
|
- name: first_statement |
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|
dtype: string |
|
|
- name: options |
|
|
struct: |
|
|
- name: arabic_keys |
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|
sequence: string |
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|
- name: english_keys |
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|
sequence: string |
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|
- name: text |
|
|
sequence: string |
|
|
- name: answer_key |
|
|
struct: |
|
|
- name: arabic_answer_key |
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|
dtype: string |
|
|
- name: english_answer_key |
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|
dtype: string |
|
|
- name: relevant_to_this_country |
|
|
dtype: string |
|
|
- name: relevant_to_other_countries |
|
|
dtype: string |
|
|
- name: should_discard |
|
|
dtype: string |
|
|
- name: country |
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|
dtype: string |
|
|
- name: region |
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|
dtype: string |
|
|
splits: |
|
|
- name: test |
|
|
num_bytes: 121372 |
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num_examples: 261 |
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download_size: 44710 |
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dataset_size: 121372 |
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- config_name: UAE |
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|
features: |
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|
- name: worker_id |
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|
dtype: string |
|
|
- name: sample_id |
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|
dtype: string |
|
|
- name: sub_topic |
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|
dtype: string |
|
|
- name: first_statement |
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|
dtype: string |
|
|
- name: options |
|
|
struct: |
|
|
- name: arabic_keys |
|
|
sequence: string |
|
|
- name: english_keys |
|
|
sequence: string |
|
|
- name: text |
|
|
sequence: string |
|
|
- name: answer_key |
|
|
struct: |
|
|
- name: arabic_answer_key |
|
|
dtype: string |
|
|
- name: english_answer_key |
|
|
dtype: string |
|
|
- name: relevant_to_this_country |
|
|
dtype: string |
|
|
- name: relevant_to_other_countries |
|
|
dtype: string |
|
|
- name: should_discard |
|
|
dtype: string |
|
|
- name: country |
|
|
dtype: string |
|
|
- name: region |
|
|
dtype: string |
|
|
splits: |
|
|
- name: test |
|
|
num_bytes: 152835 |
|
|
num_examples: 283 |
|
|
download_size: 56690 |
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|
dataset_size: 152835 |
|
|
- config_name: Yemen |
|
|
features: |
|
|
- name: worker_id |
|
|
dtype: string |
|
|
- name: sample_id |
|
|
dtype: string |
|
|
- name: sub_topic |
|
|
dtype: string |
|
|
- name: first_statement |
|
|
dtype: string |
|
|
- name: options |
|
|
struct: |
|
|
- name: arabic_keys |
|
|
sequence: string |
|
|
- name: english_keys |
|
|
sequence: string |
|
|
- name: text |
|
|
sequence: string |
|
|
- name: answer_key |
|
|
struct: |
|
|
- name: arabic_answer_key |
|
|
dtype: string |
|
|
- name: english_answer_key |
|
|
dtype: string |
|
|
- name: relevant_to_this_country |
|
|
dtype: string |
|
|
- name: relevant_to_other_countries |
|
|
dtype: string |
|
|
- name: should_discard |
|
|
dtype: string |
|
|
- name: country |
|
|
dtype: string |
|
|
- name: region |
|
|
dtype: string |
|
|
splits: |
|
|
- name: test |
|
|
num_bytes: 132363 |
|
|
num_examples: 273 |
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|
download_size: 45738 |
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dataset_size: 132363 |
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configs: |
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- config_name: Algeria |
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data_files: |
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- split: test |
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path: Algeria/test-* |
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- config_name: Egypt |
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data_files: |
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- split: test |
|
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path: Egypt/test-* |
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- config_name: Jordan |
|
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data_files: |
|
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- split: test |
|
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path: Jordan/test-* |
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- config_name: KSA |
|
|
data_files: |
|
|
- split: test |
|
|
path: KSA/test-* |
|
|
- config_name: Lebanon |
|
|
data_files: |
|
|
- split: test |
|
|
path: Lebanon/test-* |
|
|
- config_name: Libya |
|
|
data_files: |
|
|
- split: test |
|
|
path: Libya/test-* |
|
|
- config_name: Morocco |
|
|
data_files: |
|
|
- split: test |
|
|
path: Morocco/test-* |
|
|
- config_name: Palestine |
|
|
data_files: |
|
|
- split: test |
|
|
path: Palestine/test-* |
|
|
- config_name: Sudan |
|
|
data_files: |
|
|
- split: test |
|
|
path: Sudan/test-* |
|
|
- config_name: Syria |
|
|
data_files: |
|
|
- split: test |
|
|
path: Syria/test-* |
|
|
- config_name: Tunisia |
|
|
data_files: |
|
|
- split: test |
|
|
path: Tunisia/test-* |
|
|
- config_name: UAE |
|
|
data_files: |
|
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- split: test |
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path: UAE/test-* |
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- config_name: Yemen |
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data_files: |
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- split: test |
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path: Yemen/test-* |
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--- |
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# ArabCulture π¦πͺπ΅πΈπͺπ¬πΈπ¦πΎπͺπ―π΄π±π§πΈπΎπΈπ©π²π¦π©πΏπΉπ³π±πΎ |
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<p align="left"> <i>Abdelrahman Sadallah and Junior Cedric Tonga and Khalid Almubarak and Saeed Almheiri and Farah Atif and Cahtrine Qwaider and Karima Kadaoui and Sara Shatnawi and Yaser Alesh and Fajri Koto </i></p> |
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<h4 align="left"> |
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MBZUAI, SDAIA, Al-Balqa Applied University, Khalifa University |
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</h4> |
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--- |
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<p align="center"> |
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<a href="https://arxiv.org/abs/2502.12788"><img src="https://img.shields.io/badge/arXiv-2405.01535-b31b1b.svg" alt="arXiv"></a> |
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<a href="https://huggingface.co/datasets/MBZUAI/ArabCulture"><img src="https://img.shields.io/badge/Dataset-HuggingFace-yellow" alt="Hugging Face Organization"></a> |
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<a href="https://github.com/mbzuai-nlp/arab_culture/blob/main/LICENSE"><img src="https://img.shields.io/badge/License-CC--BY--NC--SA%204.0-lightgrey.svg" alt="License"></a> |
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<a href="https://github.com/mbzuai-nlp/arab_culture"> |
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<img src="https://img.shields.io/badge/GitHub-Repository-black?logo=github" alt="GitHub Repo"> |
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</a> |
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</p> |
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**ArabCulture** is a culturally grounded commonsense reasoning dataset in Modern Standard Arabic (MSA), covering 13 Arab countries across the Gulf, Levant, North Africa, and the Nile Valley. The dataset contains 3,482 multiple-choice instances that test cultural commonsense reasoning in real-world daily life situations. |
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<p align="center"> |
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<img src="./main_fig.png" alt="Logo" width="200"/> |
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</p> |
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## Dataset Summary |
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Despite the rise of Arabic LLMs, evaluation on culturally relevant reasoning has been limited. ArabCulture fills this gap with questions authored and validated by native speakers, reflecting social norms, traditions, and everyday knowledge in Arabic societies. Each instance presents a short scenario followed by three plausible sentence completions, only one of which is culturally accurate. |
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- **Language:** Modern Standard Arabic (MSA) |
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- **Countries Covered:** 13 (KSA, UAE, Yemen, Jordan, Lebanon, Syria, Palestine, Egypt, Sudan, Morocco, Algeria, Tunisia, Libya) |
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- **Domains:** 12 (e.g., food, holidays, parenting) |
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- **Subtopics:** 54 |
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- **Instances:** 3,482 |
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- **Task Type:** Multiple Choice (MCQ) and Sentence Completion |
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- **Cultural Context:** Region and country-specific |
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## Supported Tasks and Leaderboards |
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- **Commonsense Reasoning** |
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- **Cultural Knowledge Assessment** |
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- **Zero-shot Evaluation of LLMs** |
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This dataset can be used to benchmark how well Arabic or multilingual models reason within culturally specific contexts. |
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## Citation |
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``` |
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@misc{sadallah2025arabculture, |
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title={Commonsense Reasoning in Arab Culture}, |
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author={Abdelrahman Sadallah and Junior Cedric Tonga and Khalid Almubarak and Saeed Almheiri and Farah Atif and Cahtrine Qwaider and Karima Kadaoui and Sara Shatnawi and Yaser Alesh and Fajri Koto}, |
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year={2025}, |
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eprint={2502.12788}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.CL} |
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} |
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``` |
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## License |
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The ArabCulture dataset is licensed under a |
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[Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License](http://creativecommons.org/licenses/by-nc-sa/4.0/). |
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## Contact |
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For questions or contributions, contact: |
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* Abdelrahman Sadallah (abdelrahman.sadallah@mbzuai.ac.ae) |
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* Fajri Koto (fajri.koto@mbzuai.ac.ae) |