Datasets:
The dataset is currently empty. Upload or create new data files. Then, you will be able to explore them in the Dataset Viewer.
PolitTax: Document Splitting Benchmark
A benchmark for evaluating document splitting (boundary detection and classification) on U.S. presidential tax returns.
Overview
| Metric | Value |
|---|---|
| PDF files | 30 |
| Total pages | 3,311 |
| Annotated sub-documents | 1,152 |
| Classification types used | 40 |
| Subjects | Biden, Harris, Obama, Trump |
| Tax years | 2009–2023 |
Task
Given a multi-page PDF containing one or more IRS tax forms, schedules, and supplementary documents, the task is to:
- Segment the document into sub-documents by identifying start and end page boundaries
- Classify each sub-document by its form type (e.g., "Form 1040", "Schedule A (Form 1040)", "supplement")
Sub-document Type Distribution (top 10)
| Type | Count |
|---|---|
| supplement | 573 |
| misc_form | 240 |
| Schedule C (Form 1040) | 41 |
| Form 4562 | 40 |
| Schedule K-1 (Form 1065) | 33 |
| Schedule E (Form 1040) | 14 |
| Form 1065 | 14 |
| Schedule M-3 (Form 1120/1065) | 14 |
| Form 8949 | 13 |
| Form 4797 | 13 |
Files
annotations.jsonl— One JSON object per PDF with ground-truth sub-document boundariesmetadata.csv— File-level metadata (president, tax year, page count, etc.)taxonomy.json— Full classification schema with 40+ type definitions and splitting instructionspdfs/— Original PDF files organized by subject
Annotation Format
Each line in annotations.jsonl contains:
{
"file_name": "obama_2009_complete_return.pdf",
"page_count": 59,
"sub_documents": [
{
"type": "Form 1040",
"start_page": 1,
"end_page": 2,
"identifier": "Barack H. & Michelle L. Obama"
}
]
}
type: The IRS form or document type. Seetaxonomy.jsonfor the full list with descriptions.start_page/end_page: 1-indexed, inclusive page range.identifier: A human-readable label distinguishing instances of the same form type (e.g., taxpayer name, entity name).
Source
All PDFs are publicly released U.S. government records sourced from:
License
The source documents are U.S. government works in the public domain. The annotations in this dataset are released under CC0 1.0.
- Downloads last month
- 1