metadata
tags:
- document-processing
- docling
- hierarchical-parsing
- pdf-processing
- generated
PDF Document Processing with Docling
This dataset contains structured markdown extraction from PDFs in baobabtech/test-eval-documents using Docling with hierarchical parsing.
Processing Details
- Source Dataset: baobabtech/test-eval-documents
- Number of PDFs: 20
- Processing Time: 8.4 minutes
- Processing Date: 2025-12-02 15:40 UTC
Configuration
- PDF Column:
pdf_bytes - Dataset Split:
train
Dataset Structure
The dataset contains all original columns plus:
original_md: Markdown extracted by Docling (before hierarchical restructuring)hierarchical_md: Markdown with proper heading hierarchy (after hierarchical processing)sections_toc: Table of contents (one section per line, indented by level)inference_info: JSON with processing metadata
Usage
from datasets import load_dataset
dataset = load_dataset("YOUR_DATASET_ID", split="train")
for example in dataset:
print(f"Document: {example.get('file_name', 'unknown')}")
# Original markdown from Docling
print("=== Original Markdown ===")
print(example['original_md'][:500])
# Hierarchical markdown with proper heading levels
print("\n=== Hierarchical Markdown ===")
print(example['hierarchical_md'][:500])
# Table of contents
print("\n=== Table of Contents ===")
print(example['sections_toc'])
break