This package enables inference of header hierarchy in the docling PDF parsing pipeline.
Project description
docling-hierarchical-pdf
This package enables inference of header hierarchy in the docling PDF parsing pipeline.
- Github repository: https://github.com/krrome/docling-hierarchical-pdf/
- Documentation https://krrome.github.io/docling-hierarchical-pdf/
What it does:
Docling currently does not support the extraction of header hierarchies from PDF documents. This package attempts to infer and correct the hierarchy of headings based on a few simple rules and then corrects the docling Document hierarchy accordingly.
Inference
The rules are:
- Numbering-based: Attempt to infer the hierarchy from heading numbering. Arabic and roman numbering as well as outline numbering using letters.
- Style-based: If the above fails try to infer the headings by font size and style (bold / italic).
Results are as follows:
Header hierarchy before reconstruction:
Richtlinie 10-00
Einfuhrzollveranlagungsverfahren
Abkürzungsverzeichnis
1 Veranlagungsschritte im Zollveranlagungsverfahren
Ablaufschema Zollveranlagungsverfahren:
1.1 Zuführen
1.2 Zollüberwachung und Zollprüfung
1.3 Gestellen und summarisches Anmelden
1.3.1 Allgemeines
1.3.2 Form der summarischen Anmeldung
1.3.3 Manipulationen
...
After reconstruction:
Richtlinie 10-00
Einfuhrzollveranlagungsverfahren
Abkürzungsverzeichnis
1 Veranlagungsschritte im Zollveranlagungsverfahren
Ablaufschema Zollveranlagungsverfahren:
1.1 Zuführen
1.2 Zollüberwachung und Zollprüfung
1.3 Gestellen und summarisches Anmelden
1.3.1 Allgemeines
1.3.2 Form der summarischen Anmeldung
1.3.3 Manipulationen
...
Applying the hierarchy
The current solution reorders the hierarchy tree of document items according to the inference results:
- Headings become sorted into parent/child relationship as inferred from the heading hierarchy.
- Heading get assigned with the inferred heading level (
levelattribute ofSectionHeaderItem) - Any Items (except for furniture) that follow a heading become children of that last heading.
Verification
The current solution has been tested on 60+ text-based PDF documents using the docling DocumentConverter with default parameters and gave satisfying results. In an attempt to test the performance with a public dataset 20+ document from the HDRDoc dataset have been tested. This dataset is based on images so the default VLM-pipeline of docling was used. Performance was inferior to pure-text PDFs, which was limited by the performance of docling VLM-parsing.
Limitations
- The proposed solution uses the ConversionReult object rather than the DoclingDocument it produces, because DoclingDocument does not contain information on font style of text-based PDFs, which is present in the ConversionResult. The more information is available the is the inference result.
- The solution entirely relies on docling parsing - if docling does not identify a header then there is no way to get it back with this postprocessing - but docling does pretty well for text-based PDFs.
- The proposed solution currently does not take TOC-bookmarks into account, but I am planning to integrate that soon.
- The proposed solution has not yet been evaluated on the full HRDoc dataset, but I am planning to do this soon.
How to use it:
Install it:
pip install XXXX
Use it:
from docling.document_converter import DocumentConverter
from hierarchical.postprocessor import ResultPostprocessor
source = "my_file.pdf" # document per local path or URL
converter = DocumentConverter()
result = converter.convert(source)
# the postprocessor modifies the result.document in place.
ResultPostprocessor(result).process()
# enjoy the reordered document
result.document.export_to_markdown()
Citation
If you use this software for your project please cite Docling as well as the following:
@software{docling_hierarchical,
author = {Roman, Kayan},
month = {09},
title = {{docling-hierarchical-pdf}},
url = {https://github.com/krrome/docling-hierarchical-pdf},
version = {0.0.1},
year = {2025}
}
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