OpenDataLoaderTagged PDF
Using native PDF structure tags for accurate AI data extraction and accessibility compliance
Why Tagged PDF Matters for AI
Tagged PDF includes semantic structure (headings, paragraphs, lists, tables) that tells AI exactly how a document is organized. When a PDF has proper tags, you get:
- Exact layout intent — No guessing, no heuristics
- Correct reading order — Author's intended flow preserved
- Semantic hierarchy — Headings, lists, tables properly identified
Accessibility Regulations
Multiple regulations now require accessible digital documents, driving widespread adoption of Tagged PDF. Key regulations include the European Accessibility Act (EAA), ADA/Section 508 (USA), and similar laws in other jurisdictions.
See Accessibility Compliance for details.
OpenDataLoader leverages this shift — when structure tags exist, we extract the exact layout the author intended, without guessing.
How to Use Tagged PDF
Enable Tagged PDF extraction with the use_struct_tree option:
import opendataloader_pdf
# Batch all files in one call — each convert() spawns a JVM process, so repeated calls are slow
opendataloader_pdf.convert(
input_path=["file1.pdf", "file2.pdf", "folder/"],
output_dir="output/",
use_struct_tree=True # Use native PDF structure tags
)Most PDF parsers ignore structure tags entirely. OpenDataLoader is one of the few that fully supports them.
CLI Usage
# Batch all files in one call — each invocation spawns a JVM process, so repeated calls are slow
opendataloader-pdf file1.pdf file2.pdf folder/ \
--output-dir output/ \
--use-struct-treeChecking if a PDF is Tagged
If a PDF lacks structure tags, OpenDataLoader logs a warning and falls back to visual heuristics (XY-Cut++ algorithm). Check your logs for:
WARN: Document lacks structure tree, falling back to visual heuristicsDevelopment Status
| Feature | Purpose | Status |
|---|---|---|
| Tag extraction | Use existing tags to determine document structure | Available |
| Auto-Tagging Engine | Generate structure tags for untagged PDFs | Available |
| Tag validation | Validate tags against PDF Association recommendations | In progress |
| PDF/UA Validation | Verify compliance with PDF/UA standards | Q3 2026 |
| Hybrid extraction | Combine tags with visual heuristics for best results | In progress |
Use Cases
Research Papers
A well-tagged paper lets AI accurately identify author names, affiliations, and sections — enabling automated citation building.
Financial Reports
Proper tags enable precise extraction of balance sheet titles and data cells, automating analysis without error-prone heuristics.
Legal Contracts
Tags help AI quickly identify and cross-reference clauses, dates, and parties — speeding up legal review.
Learn More
- Tagged PDF for RAG — Optimizing extraction for AI pipelines
- Accessibility Compliance — EAA, ADA, and regulatory requirements
- PDF Accessibility Glossary — Key terms and concepts
- Industry Collaboration — Based on PDF Association specifications, developed with Hancom and Dual Lab