Create README.md

README.md

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+---
+license: apache-2.0
+task_categories:
+- question-answering
+- text-generation
+- text-classification
+- table-question-answering
+language:
+- en
+- hi
+tags:
+- finance
+- synthetic
+- india
+- Tax
+- taxation
+- itr
+- document-ai
+- financial-documents
+pretty_name: Indian-Income-Tax-Returns
+size_categories:
+- n<1K
+---
+# Indian Income Tax Return Synthetic Dataset
+
+A fully synthetic, high-fidelity dataset of **Indian Income Tax Return forms (ITR-4, ITR-5, and ITR-6)**.  Designed to support OCR, text extraction, table parsing, tax attribute detection, document intelligence, and LLM fine-tuning for structured data extraction. Each record includes a **PDF tax return** and a matching structured **JSON file** containing parsed fields.
+
+This dataset simulates realistic taxpayer filings across:
+
+- Individuals (with Aadhaar and father’s name)
+- Partnership firms (with partner names)
+- Companies (with director details)
+
+It also models real-world financial variation including **refund cases, NIL returns, payable balances, late filings, interest under 234A/B/C, cess calculations, and filing statuses (139(1)/139(4)).**
+
+## Dataset Details
+
+- **Curated by:** AgamiAI Inc.
+- **Language(s):** English, Hindi (romanized)
+- **License:** Apache 2.0
+- **Repository:** https://huggingface.co/datasets/AgamiAI/Indian-Income-Tax-Returns
+- **Website:** https://www.agami.ai
+
+**Note:** This dataset contains no real taxpayer data. All identities, values, and addresses are algorithmically generated.
+
+## Uses
+
+### Suitable For
+- Document AI and OCR R&D
+- Key-value and table extraction
+- Named Entity Recognition (NER) for financial documents
+- Tax computation extraction and validation workflows
+- Layout-aware LLM fine-tuning (Donut, LayoutLMv3, SmolDoc, Nougat)
+- Benchmarking structured extraction pipelines
+- Multi-page form parsing and field alignment testing
+
+### Not Suitable For
+- Real-world tax reporting or compliance
+- Fraud detection or audit-based analytics (no fraudulant patterns)
+- Socioeconomic or demographic analysis
+- Real-world tax policy modeling
+
+## Dataset Structure
+
+### Statement Formats
+
+| ITR Form | Entity Type | Description |
+|----------|-------------|-------------|
+| **ITR-4** | Individuals with business income | Includes Aadhaar, father's name, basic income schedules |
+| **ITR-5** | Firms / LLPs | Includes partner name, tax computation, interest schedules |
+| **ITR-6** | Companies | Includes director name, business income, cess & interest |
+
+
+### JSON Structure
+
+```json
+{
+  "name": "NOVA EXPORTS",
+  "entity": "Firm",
+  "form": "ITR-5",
+  "pan": "AQCPN5123F",
+  "assessment_year": "2024-25",
+  "filing_timestamp": "2024-11-18 14:23:55",
+  "filing_type": "139(4) - Belated",
+  "signatory": "Rajesh Singh",
+  "dob": "14-Aug-1979",
+  "address": "Sector 31, Gurgaon, Haryana - 122005",
+  "income": 8235000,
+  "tax": 2470500,
+  "cess": 98820,
+  "interest": {
+    "234A": 28000,
+    "234B": 51000,
+    "234C": 42000
+  },
+  "total_payable": 2649320,
+  "taxes_paid": 2650000,
+  "balance": 680
+}
+```
+
+## Included Variation
+
+This dataset contains controlled variation to simulate realistic diversity found across Indian income tax filings.
+
+- **Entity Types:** Individuals, Firms, Companies  
+- **Geographies:** Major Indian metros and tier-2 cities  
+- **Tax Outcomes:** Refund cases, NIL returns, and payable outstanding amounts  
+- **Filing Types:** On-time, revised, and belated submissions (u/s 139(4))  
+- **Document Formatting:** Variation in layout structure, addresses, dates, names, and signatory styles  
+
+### Value Ranges
+
+| Category | Range | Notes |
+|----------|-------|-------|
+| **Income** | ₹4,00,000 → ₹20,00,00,000+ | Scaled by entity type |
+| **Filing Years** | AY 2022–2026 | Randomized across dataset |
+| **Signatory Age** | 25–75 years | Professionally realistic |
+| **Interest & Cess Calculations** | Randomized + rule-based | Includes Sections 234A/234B/234C + 4% cess |
+
+
+## Dataset Creation
+
+### Why This Dataset Exists
+
+Real Indian income tax return datasets are highly sensitive, protected by law, and not publicly available for machine learning research.  
+This synthetic dataset is created to fill that gap and enable:
+
+- Training and benchmarking **Document AI / OCR systems**
+- Layout-aware extraction and key-value pair modeling
+- Building and testing fintech and compliance automation systems
+- Research and education in AI for structured financial documents
+- Evaluation of LLMs on financial form understanding
+
+---
+
+### How It Was Generated
+
+This dataset is fully algorithmically constructed using controlled randomness and rule-based logic, including:
+
+- **Procedural synthetic generation of taxpayer profiles**
+- **Rule-driven fiscal computation and formatting**
+- **Entity-specific metadata modeling** (Individuals, Firms, Companies)
+- **Probabilistic variation in names, filing types, and geographies**
+- **Digitally rendered PDF layouts with watermark and formatting diversity**
+- **JSON output aligned directly with visible PDF values**
+
+All data is artificial — no real taxpayer information, PAN numbers, Aadhaar values, or confidential records were used.
+
+
+### What's Included
+
+- **Account holders:** Business entities (companies, partnerships, corporations)
+- **Transaction patterns:** B2B payments, employee salaries, vendor payments, business expenses
+- **Regional diversity:** Major Indian metros
+- **Temporal patterns:** Quarterly statements, monthly salary cycles, vendor payment patterns
+
+## Limitations
+
+## Limitations
+
+1. **No real taxpayer data** — Does not reflect true economic or demographic patterns  
+2. **Simplified tax logic** — Does not include deductions (80C, HRA), exemptions, MAT/AMT, surcharge tiers, or capital gains schedules  
+3. **Entity coverage scope** — Includes only Individuals (business income), Firms, and Companies; excludes trusts, NGOs, foreign asset disclosures, or complex corporate filings  
+4. **Format coverage** — Modeled on common ITR layouts; does not represent every version, annexure, or legacy revision  
+5. **Synthetic reasoning constraints** — Does not cover all real-world edge cases  
+6. **OCR realism** — May not include all real-world OCR challenges
+7. **Regulatory compliance** — Not suitable for legal, taxation, or compliance workflows without real data validation  
+
+
+This dataset is for structure and format learning, not behavioral modeling. Always validate on real data before production deployment.
+
+## Citation
+
+**BibTeX:**
+
+```bibtex
+@dataset{indian_income_tax_return_synthetic_2025,
+  author = {AgamiAI Inc.},
+  title = {Indian Income Tax Return Synthetic Dataset},
+  year = {2025},
+  publisher = {HuggingFace},
+  url = {https://huggingface.co/datasets/AgamiAI/Indian-Income-Tax-Returns}
+}
+```
+
+**APA:**
+
+AgamiAI Inc. (2025). *Indian Income Tax Return Synthetic Dataset* [Data set]. HuggingFace. https://huggingface.co/datasets/AgamiAI/Indian-Income-Tax-Returns
+
+## Glossary
+
+## Glossary
+
+**Indian Taxation Terms:**
+- **AY (Assessment Year):**  
+  The year in which income earned in the previous financial year is assessed and taxed.
+- **FY (Financial Year):**  
+  The period in which income is earned — from **1 April to 31 March**.
+- **ITR (Income Tax Return):**  
+  The official form used to report income, taxes paid, and tax liability.
+- **PAN (Permanent Account Number):**  
+  A 10-character alphanumeric tax identifier issued by the Government of India.
+- **Aadhaar:**  
+  A 12-digit resident identification number issued by UIDAI (included only for individuals).
+- **ITR-4:**  
+  Return form used by individuals/HUFs declaring presumptive business income.
+- **ITR-5:**  
+  Return form applicable for partnership firms, LLPs, and certain associations.
+- **ITR-6:**  
+  Return form for companies (except those claiming exemption under Section 11).
+- **139(1):**  
+  Return filed **on or before** the due date.
+- **139(4):**  
+  **Belated return** filed after the due date.
+- **Health & Education Cess:**  
+  A mandatory **4%** surcharge applied on calculated tax liability.
+- **Self-Assessment Tax:**  
+  Tax paid by the taxpayer before filing, when advance tax/TDS isn't sufficient.
+- **Refund:**  
+  Amount returned to the taxpayer if tax paid exceeds the computed liability.
+- **Tax Payable:**  
+  Outstanding tax amount due after accounting for advance tax, TDS/TCS, and credit adjustments.
+- **Interest u/s 234A:**  
+  Charged for **late filing** of the income tax return.
+- **Interest u/s 234B:**  
+  Levied for **not paying adequate advance tax**.
+- **Interest u/s 234C:**  
+  Applied for **late installment payment** of advance tax.
+- **Verification Section:**  
+  Mandatory declaration signed digitally or manually by the taxpayer or authorized signatory.
+
+
+## More Information
+
+### About AgamiAI
+
+AgamiAI builds private AI solutions for enterprises where privacy, accuracy, and compliance are critical. Specialized in Finance, Healthcare, Legal, and Consulting.
+
+Visit: **https://www.agami.ai**
+
+### File Structure
+
+Each ITR Document includes:
+- `[ITR_id].pdf` - Scanned Income Tax Return (first two pages)
+- `[ITR_id].json` - Structured data with full metadata
+
+### Related Datasets
+
+Part of AgamiAI's Indian Financial Documents collection:
+- Indian Bank Statements (https://huggingface.co/datasets/AgamiAI/Indian-Bank-Statements)
+- **Indian Income Tax Returns** (this dataset)
+- Indian GST Documents (coming soon)
+- Indian Audited Financial Documents (coming soon)
+
+### Contact
+
+- **Website**: https://www.agami.ai
+- **HuggingFace**: https://huggingface.co/AgamiAI
+
+---
+
+**Version:** 1.0.0 | **License:** Apache 2.0 | **Last Updated:** December 2025
+
+**Privacy Notice:** Entirely synthetic data. No real personal or financial information included.