---
language:
- ckb
- ku
license: apache-2.0
size_categories:
- 18K<n<28K
task_categories:
- text-generation
---
# Kurdish Books Dataset with Combined Text Field

## Dataset Description

This dataset contains 18,565 Kurdish books with a combined text field that includes author, book name, title, and content in a structured format. All text has been preprocessed using the asosoft library.

### Languages

- Central Kurdish (ckb)
- Kurdish (ku)

### Dataset Structure

The dataset contains the following columns:
- `author`
- `book`
- `title`
- `url`
- `content`
- `text`

### Text Field Format

The `text` column combines all metadata and content in the following Kurdish format:

```
[author] لە کتێبی [book] ناوەڕۆکی [title] :
[content]
```

This format makes it easy to use the entire record as a single text input for language models.

### Data Processing

#### Text Column Creation
A new `text` column was created by combining:
- Author name
- Book title (with Kurdish connector "لە کتێبی")
- Chapter/section title (with Kurdish connector "ناوەڕۆکی")
- Main content

#### Text Preprocessing
Both the `content` and `text` columns were preprocessed using the [asosoft](https://github.com/KurdishNLP/asosoft) library:
1. **Text normalization** (`asosoft.Normalize`) - Standardizes Kurdish characters
2. **Punctuation normalization** (`asosoft.NormalizePunctuations`) - Standardizes punctuation
3. **Line trimming** (`asosoft.TrimLine`) - Removes extra whitespace

### Example Usage

```python
from datasets import load_dataset

# Load the dataset
dataset = load_dataset("shiima/vejin-Dataset-Normalization-with-textColumn")

# View a sample
sample = dataset['train'][0]
print(f"Author: {sample['author']}")
print(f"Book: {sample['book']}")
print(f"Title: {sample['title']}")
print(f"\nCombined Text:\n{sample['text']}")

# Use the text field for language model training
for sample in dataset['train']:
    text = sample['text']
    # Train your model with this text
    print(text[:100])
    break
```

### Use Cases

This dataset is suitable for:
- Kurdish language model pretraining
- Kurdish text generation
- Kurdish question answering
- Kurdish book understanding
- Kurdish NLP research
- Document retrieval and search
- Kurdish literature analysis

### Statistics

- **Total Samples**: 18,565
- **Languages**: Kurdish (Central Kurdish, Kurmanji)
- **Script**: Arabic script
- **Format**: Structured book data with combined text field
- **Columns**: 6 (author, book, title, url, content, text)

### Data Fields

- **author**: Name of the book's author
- **book**: Book name or identifier
- **title**: Title of the text/chapter/section
- **url**: Source URL or reference (if available)
- **content**: Main text content (preprocessed)
- **text**: Combined field with author, book, title, and content in Kurdish format (preprocessed)

### Quality

All text fields have been preprocessed to ensure:
- Consistent Kurdish character encoding
- Standardized punctuation
- Clean text suitable for NLP applications
- Removed formatting artifacts

### Text Field Advantages

The combined `text` field provides:
- Ready-to-use format for language model training
- Contextual information (author and book) included with content
- Natural Kurdish language structure
- Easy to use without additional formatting

### Source

This dataset was created from an Excel file containing Kurdish book data. Text fields were preprocessed using asosoft for improved quality.

### Citation

If you use this dataset, please acknowledge:
- The asosoft preprocessing library: [asosoft](https://github.com/KurdishNLP/asosoft)
- The original book sources

### License

Apache 2.0 (or specify your license)

### Acknowledgments

- Preprocessing library: [asosoft](https://github.com/KurdishNLP/asosoft) by Kurdish NLP
- Original book authors and sources
- Kurdish NLP community

### Notes

- The `text` field combines all information in a natural Kurdish format
- All text has been preprocessed for consistency
- Suitable for various Kurdish NLP tasks
- Ready for language model training without additional processing

### Contact

For questions or issues, please open an issue on the dataset repository.