Kurdish-Dataset

This repository aims to be a comprehensive dataset written in the Kurdish language, sourced from various materials. The resulting dataset will facilitate diverse studies on the Kurdish language.

Repository Contents

Data Directory

The data folder is the main container for dataset-related files. It is organized into three subfolders:

• data_files: Contains data tables (e.g., PDFs) to be added to the dataset.
• raw: Serves as a backup folder. It includes:
  • raw_kurmanji.txt: Stores unprocessed text extracted using the PDFTextExtractor from pdf_to_text.py. This file is used for manual review and corrections before processing.
• processed: The final output folder, containing:
  • kurmanji.txt: The plain text file of the final dataset.
  • kurmanji.json: The JSON representation of the final dataset, automatically populated with the following fields:
    • file_name: The source file name.
    • char_count: The character count of the text.
    • word_count: The word count of the text.
    • text: The actual text content.

Scripts Directory

The scripts folder contains:

• pdf_to_text.py: A script to convert PDF files to text.

Main Script

main.py is the primary Python script, enabling streamlined data integration without dealing directly with intermediate processing scripts. Below is an example usage:

from scripts.pdf_to_text import PDFTextExtractor

# Converts the PDF file to text and transfers it to data/raw/raw_kurmanji.txt for manual review.
pdftextextractor = PDFTextExtractor("data/data_files/file_name.pdf")

# After manual review, the final data is transferred to kurmanji.txt and kurmanji.json.
pdftextextractor.append_raw_to_processed_data()

Data Integration Workflow

1. Add the desired file to the data/data_files directory.
2. Use the PDFTextExtractor class to extract raw text:

   pdftextextractor = PDFTextExtractor("data/data_files/file_name.pdf")

   The extracted text will be saved in data/raw/raw_kurmanji.txt for manual review.
3. Manually review and correct the contents of data/raw/raw_kurmanji.txt.
4. Transfer the reviewed data to the processed files:

   pdftextextractor.append_raw_to_processed_data()

   The reviewed data will be appended to data/processed/kurmanji.txt and data/processed/kurmanji.json.

Customizing Page Ranges

The PDFTextExtractor class supports two optional parameters: start_page and end_page. These parameters allow users to specify the range of pages to extract text from a PDF. By default, both parameters are None, meaning the entire PDF is processed. To process specific pages, specify the range as shown below:

pdftextextractor = PDFTextExtractor("data/data_files/file_name.pdf", start_page=1, end_page=5)