---
name: Persian Poetry QA Dataset
description: |
    This dataset is structured in a question-answering format derived from a rich collection of Persian poems along with metadata about the poets and the verses. 
    It is designed to be utilized for various Natural Language Processing and analysis tasks related to Persian poetry, such as Question Answering, Text Generation, Language Modeling, and Style Analysis.
license: gpl-2.0
url: https://github.com/ganjoor/desktop/releases/tag/v2.81
citation: |
    Persian Poetry QA Dataset. Collected by Kakooch from the Ganjoor Project.
    Available at: https://huggingface.co/datasets/persian_poetry
size: "Custom"
language: 
    - fa
splits:
    train:
        description: "This split contains Persian poems structured for QA, where each row asks for a sample poem from a specific poet with the poem or verse as the answer."
features:
    context:
        description: "A static string which is 'Persian Poetry or شعر فارسی'."
        type: "string"
    question:
        description: "A string that asks for a sample poem from a specific poet in the format 'یک نمونه از شعر [POET_NAME]'."
        type: "string"
    answer:
        description: "Text of a hemistich or verse."
        type: "string"
    answer_start:
        description: "The starting character index of `answer` within `context` (Note: this is always -1 in the current dataset as `answer` is not a substring of `context`)."
        type: "int32"
configs:
- config_name: default
  data_files:
  - split: train
    path: poems-qa.csv
---
# Persian Poetry Dataset

## Dataset Description

### Overview

This dataset contains a collection of Persian poems structured in a question-answering format. The dataset is derived from various Persian poets and their poems, providing a rich source for exploring Persian poetry in a structured manner suitable for machine learning applications, especially in natural language processing tasks like question answering.

### Data Collection

- **Data Collection Source:** The data is sourced from the [Ganjoor project](https://github.com/ganjoor/). The specific database file can be found in the [releases section](https://github.com/ganjoor/desktop/releases/tag/v2.81) of their GitHub repository.
- **Time Period:** Oct-12-2023
- **Collection Methods:** The data was collected by downloading the raw database file from the Ganjoor project's GitHub repository.

### Data Structure

The dataset is structured into a CSV file with the following columns:
- `context`: A static string which is "Persian Poetry or شعر فارسی".
- `question`: A string that asks for a sample poem from a specific poet in the format "یک نمونه از شعر [POET_NAME]".
- `answer`: Text of a hemistich or verse.
- `answer_start`: The starting character index of `answer` within `context` (Note: this is always -1 in the current dataset as `answer` is not a substring of `context`).

### Data Example

```plaintext
context,question,answer,answer_start
Persian Poetry,یک نمونه از شعر صائب تبریزی,خار نتواند گرفتن دامن ریگ روان 	 رهنورد شوق، افسردن نمی داند که چیست,-1
```

## Dataset Usage

### Use Cases

This dataset can be utilized for various Natural Language Processing and analysis tasks related to Persian poetry, such as:
- Question Answering
- Text Generation
- Language Modeling
- Style Analysis

### Challenges & Limitations

- The `answer_start` field is always -1 as the `answer` is not a substring of `context`. Depending on your use-case, you might need to adjust how `context` and `answer_start` are determined.
- The dataset does not contain long verses that are over 100 characters.

### License

GPL-2 (GNU General Public License) ingerited from original ganjoor project 

## Additional Information

### Citation

```
Persian Poetry Dataset. Collected by Kakooch from the Ganjoor Project. Available at: https://huggingface.co/datasets/persian_poetry
```

### Dataset Link 

[Download the dataset from Hugging Face](https://huggingface.co/datasets/persian_poetry)

### Contact 

Email: [kakooch@gmail.com](mailto:kakooch@gmail.com) | GitHub: [kakooch](https://github.com/kakooch)

---

*This README was generated by Kakooch.*