metadata
annotations_creators:
- expert-annotators
language_creators:
- found
language:
- mr
- hi
- en
license: cc-by-4.0
task_categories:
- document-question-answering
- table-question-answering
- image-to-text
tags:
- indic-nlp
- document-ai
- ocr-benchmark
- indian-government-documents
- document-layout-analysis
- visual-text-recognition
size_categories:
- n<1K
IndicGovBench-Doc: Comprehensive Benchmark for Indian Government Documents
IndicGovBench-Doc is an evaluation benchmark for document understanding, optical character recognition (OCR), visual layout analysis, and table extraction across Indian government administrative documents (Government Resolutions, Gazettes, Circulars, Certificates).
Dataset Summary
- Documents: 270 full-page official government records.
- Languages: Marathi (Mr), Hindi (Hi), English (En), and multi-lingual codeswitching.
- Annotations: High-density bounding box segmentation under RFC-style annotation protocol v0.9.
- Multi-column reading order.
- Complex nested and irregular table structures.
- Explicit scope boundaries:
target,excluded,uncertain. - Word-level spatial anchors aligned with Google Cloud Vision.
Dataset Structure
Each row in the dataset corresponds to a document page:
doc_id: Unique identifier (e.g.order_mr_archive_001).language: Primary language (mr,hi,en).doc_category: Document category (archive,current,gazette, etc.).width,height: Canvas pixel dimensions.content_bbox: Bounding box of all valid content[min_x, min_y, max_x, max_y].ground_truth_blocks: Structured text blocks with category, polygon, text, and reading order.ground_truth_tables: Table data with HTML, markdown, rows, cols, and cell grids.metadata: Outward number, date, department, and scan quality strata.
Citation
@dataset{indicgovbench2026,
author = {Orgpedia Foundation},
title = {IndicGovBench-Doc: Benchmark for Indian Government Document Processing},
year = {2026},
publisher = {Hugging Face},
howpublished = {\url{https://huggingface.co/datasets/Orgpedia/indicGovBench-Doc}}
}