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farbodbij/Ganjoor-Corpus

English | فارسی Ganjoor-Corpus The Ganjoor poetry corpus as four tables covering poems, books of poetry, and poet information. This corpus can be used for training models, statistical work, and building other datasets. Configs poets: 234 poets. field description poet_id Ganjoor poet id name, nickname full name and pen name url Ganjoor path birth_year, death_year lunar Hijri; birth_year_valid / death_year_valid say whether Ganjoor marks the date as… See the full description on the dataset page: https://huggingface.co/datasets/farbodbij/Ganjoor-Corpus.

sourceHugging Faceotherupdated 1mo agoView on Hugging Face

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Dataset Card

English | فارسی

Ganjoor-Corpus

The Ganjoor poetry corpus as four tables covering poems, books of poetry, and poet information. This corpus can be used for training models, statistical work, and building other datasets.

Configs

`poets`: 234 poets.

field	description
`poet_id`	Ganjoor poet id
`name`, `nickname`	full name and pen name
`url`	Ganjoor path
`birth_year`, `death_year`	lunar Hijri; `birth_year_valid` / `death_year_valid` say whether Ganjoor marks the date as reliable
`birth_place`, `death_place`	as given by Ganjoor
`description`	poet biography

`categories`: where a poem sits in the Ganjoor category tree, including book name, section within the book, and the rest.

field	description
`cat_id`	Ganjoor category id
`parent_id`	parent category; null at the poet root
`poet_id`	owning poet
`title`, `url`	category title and path
`book_name`	filled when Ganjoor sets it on the poet root (e.g. دیوان حافظ)
`description`	category note, if any
`depth`	0 poet, 1 work (گلستان, شاهنامه, غزلیات), deeper = chapter

`poems` (default): 132,591 poems.

field	description
`poem_id`	Ganjoor poem id
`poet_id`	Ganjoor poet id
`cat_id`	leaf folder
`book_id`	work-level category (`depth` 0 or 1)
`title`, `full_title`, `url`	poem title and path
`rhythm`, `metre_id`	aruz string and metre id, empty when Ganjoor has none
`rhyme`	`RhymeLetters`
`poem_format`	form from poem sections (e.g. Ghazal, Masnavi); `	` if mixed
`language`	Ganjoor language tag when present
`source`	text source name on Ganjoor
`summary`, `summary_is_ai`	poem summary; `summary_is_ai` is true when it starts with «هوش مصنوعی»
`couplet_count`	number of rows this poem contributes to `couplets`

HTML is not included. 127,695 of 129,414 summaries are AI-generated.

`couplets`: 1,488,130 beyts. One row per couplet, each mesra in its own column.

field	description
`first`, `second`	the two mesras of the couplet
`poem_id`, `poet_id`	join keys
`couplet_index`	couplet number within the poem (Ganjoor `CoupletIndex`)

Right / CenteredVerse1 → first; Left / CenteredVerse2 → second. Paragraphs and comments are omitted (80,555 prose verses). An unpaired mesra is kept with an empty second (4,859 rows).

python

from datasets import load_dataset

poems = load_dataset("farbodbij/Ganjoor-Corpus", "poems", split="train")
couplets = load_dataset("farbodbij/Ganjoor-Corpus", "couplets", split="train")
poets = load_dataset("farbodbij/Ganjoor-Corpus", "poets", split="train")
categories = load_dataset("farbodbij/Ganjoor-Corpus", "categories", split="train")

How it was built

Fields in this dataset (metre, rhyme, format, summaries, biographies, and the rest) are taken from Ganjoor as-is, with no correction or rewriting. Their accuracy therefore depends on the accuracy of Ganjoor’s data.

Thanks Disclaimer

We are thankful to Ganjoor team for releasing their meticulously curated data publicly, allowing anyone to deliver high-quality Persian datasets to the NLP community. This both helps Persian as a low-resource language and also contributes to distribution of the Iranian culture.