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---
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license: mit
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task_categories:
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- question-answering
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language:
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- fa
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size_categories:
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- 1K<n<10K
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---
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## Dataset Information
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This Question Answering dataset is a reading comprehension resource derived from Persian Wikipedia. This crowd-sourced dataset contains over 9,000 entries, each of which can either be an unanswerable question or a question with one or more answers based on the provided context. Similar to the SQuAD2.0 dataset, the inclusion of unanswerable questions allows for the development of systems that "know they don't know the answer." Additionally, the dataset includes 900 test samples. Initial models trained on this dataset, specifically using Transformers, are also accessible. All contributors to the dataset are native Persian speakers. Notably, the contexts encompass a wide range of topics from various Wikipedia categories, including History, Religion, Geography, Science, and more. Currently, each context features 7 question-and-answer pairs along with 3 unanswerable questions.
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---
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language:
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- fa
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license:
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- mit
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multilinguality:
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- monolingual
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size_categories:
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- 1K<n<10K
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task_categories:
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- question-answering
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---
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## Dataset Information
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This Question Answering dataset is a reading comprehension resource derived from Persian Wikipedia. This crowd-sourced dataset contains over 9,000 entries, each of which can either be an unanswerable question or a question with one or more answers based on the provided context. Similar to the SQuAD2.0 dataset, the inclusion of unanswerable questions allows for the development of systems that "know they don't know the answer." Additionally, the dataset includes 900 test samples. Initial models trained on this dataset, specifically using Transformers, are also accessible. All contributors to the dataset are native Persian speakers. Notably, the contexts encompass a wide range of topics from various Wikipedia categories, including History, Religion, Geography, Science, and more. Currently, each context features 7 question-and-answer pairs along with 3 unanswerable questions.
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