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- ---
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- license: gpl-2.0
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ license: gpl-2.0
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+ tags:
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+ - code
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+ - Arabic
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+ - arabic_pems
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+ - NLP
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+ - poetry
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+ - AI
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+ - text_generation
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+ - text_to_speech
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+ - digital_humanities
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+ - data_analysis
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+ - literary_analysis
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+ - machine_learning
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+ - cultural_heritage
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+ - arabic_literature
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+ - poem_classification
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+ - language_model
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+ - data_science
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+ - audio_visualization
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+ - educational_tools
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+ - computational_linguistics
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+ ---
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+ Arabic Poems
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+ it's a filtered version for (https://huggingface.co/datasets/arbml/ashaar) with only al-diwan data
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+ Overview:
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+ The "Arabic Poems" dataset is a comprehensive collection of Arabic poetry, comprising 8,875 entries. Each entry contains detailed information about individual poems and their respective poets, making it a valuable resource for researchers, developers, and enthusiasts of Arabic literature.
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+
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+ Columns:
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+
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+ Unnamed: 0: An index column.
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+ poem_title: The title of the poem.
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+ poem_meter: The poetic meter used in the poem.
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+ poem_verses: The verses of the poem, stored as strings representing lists of individual lines.
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+ poem_theme: The theme of the poem (e.g., religious, satirical, general).
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+ poet_name: The name of the poet.
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+ poet_description: A brief description of the poet, including their background and significance.
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+ poet_era: The era in which the poet lived and composed their works (e.g., Ottoman era).
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+ Usage:
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+ This dataset can be used to train and evaluate natural language processing (NLP) models for various tasks such as text generation, sentiment analysis, and poetry classification. It is particularly suitable for applications in AI poetry generation, where the model can take a poem's title and produce the poem's text, accompanied by visual and audio presentations.
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+ This dataset enables the development of innovative AI tools like [Al-Asmai](https://github.com/alwalid54321/Al-Asmaai/): The Digital Poet, which transforms Arabic poem into complete poetic texts and converts these texts into engaging visual and audio presentations. ​