README.md

---
license: cc-by-4.0
language:
- en
tags:
- legal
- india
- rti
- right-to-information
- administrative-law
- nlp
- classification
- dataset
- civic-ai
pretty_name: RTI-Bench
size_categories:
- 1K<n<10K
task_categories:
- text-classification
- summarization
- question-answering
---

# RTI-Bench: A Structured Dataset for Indian RTI Decision Analysis

## Dataset Description

RTI-Bench is the first structured dataset of Central Information Commission (CIC) decisions under India's Right to Information Act, 2005. It supports research in legal NLP, civic AI, and AI-assisted access to justice.

**Total cases: 1,516** across two sources:
- **1,218** annotated instruction-response pairs (Source A)
- **298** structured CIC PDF decisions spanning 5 commissioners and 3 document format generations, 2023–2026 (Source B)

**Overall label coverage: 82.8%** of 1,457 primary cases, extracted using a fully reproducible rule-based pipeline — no LLM annotation.

---

## Dataset Structure

### Source A — Instruction-Response Corpus (`hf_annotated`)

Derived from `jatinmehra/RTI-CASE-DATASET` with structured fields added via rule-based extraction.

| Field | Type | Description |
|-------|------|-------------|
| `hf_id` | int | Original row index |
| `title` | string | RTI case subject line |
| `instruction` | string | Background: information sought, PIO response, hearing |
| `response` | string | Commission's final direction |
| `public_authority` | string | Government department/body |
| `information_sought` | string | What the RTI requested (1 sentence) |
| `exemptions_cited` | list[string] | RTI Act sections invoked e.g. `["8(1)(j)"]` |
| `outcome` | string | See outcome labels below |
| `penalty_inr` | float | Penalty amount if imposed |
| `compensation_inr` | float | Compensation awarded if any |
| `final_direction` | string | Last directive sentence from Commission |

### Source B — CIC PDF Corpus (`cic_annotated`)

Extracted from 298 CIC decision PDFs collected from dsscic.nic.in.

| Field | Type | Description |
|-------|------|-------------|
| `filename` | string | Original PDF filename |
| `doc_subtype` | string | PRIMARY_DECISION / ADJUNCT_COMPLIANCE / FULL_BENCH |
| `doc_format` | string | 2023a / 2023b / 2026 |
| `case_no` | string | CIC case number e.g. `CIC/CSWRI/A/2021/136051` |
| `commissioner` | string | Information Commissioner name |
| `public_authority` | string | Respondent department |
| `issue` | string | Information sought (IRAC Issue component) |
| `application` | string | Submissions during hearing (IRAC Application) |
| `rules_cited` | list[string] | RTI Act sections referenced |
| `conclusion` | string | Commission's decision text (IRAC Conclusion) |
| `outcome` | string | See outcome labels below |
| `exemptions_cited` | list[string] | Section 8(1)(x) exemptions invoked |
| `rti_filed_on` | string | Date RTI application filed |
| `cpio_replied_on` | string | Date CPIO replied |
| `first_appeal_on` | string | Date first appeal filed |
| `date_of_hearing` | string | Date of CIC hearing |
| `adjunct_outcome` | string | For ADJUNCT_COMPLIANCE: SCN_DROPPED / PENALTY_IMPOSED etc. |

---

## Outcome Labels

| Label | Description | Count (A) | Count (B) |
|-------|-------------|-----------|-----------|
| `INFORMATION_DIRECTED` | Commission directed disclosure | 524 | 15 |
| `APPEAL_DISMISSED` | Appeal dismissed, PIO upheld | 380 | 69 |
| `UNKNOWN` | Requires human review | 134 | 117 |
| `PENALTY_IMPOSED` | Penalty under Section 20 | 92 | 10 |
| `PARTIAL_RELIEF` | Partial information directed | 76 | 0 |
| `COMPLAINT_S18` | Section 18 complaint disposed | 0 | 18 |
| `REMANDED` | Referred back to PIO/FAA | 11 | 5 |
| `WITHDRAWN` | Appellant withdrew | 0 | 5 |
| `ADJOURNED` | Adjourned sine die | 1 | 0 |

---

## Exemption Distribution

467 total exemption citations across both sources:

| Section | Description | Count |
|---------|-------------|-------|
| 8(1)(j) | Personal information | 158 |
| 8(1)(d) | Commercial confidence | 77 |
| 8(1)(e) | Fiduciary relationship | 76 |
| 8(1)(h) | Impeding investigation | 71 |
| 8(1)(g) | Life/safety of person | 31 |
| 8(1)(a) | Sovereignty/security | 25 |
| 8(1)(i) | Cabinet papers | 16 |
| 8(1)(c) | Parliament privilege | 6 |
| 8(1)(b) | Contempt of court | 5 |
| 8(1)(f) | Fiduciary (foreign govt) | 2 |

---

## Benchmark Tasks

RTI-Bench supports four benchmark tasks:

**Task 1 — Outcome Prediction**
Given the background narrative, predict the Commission outcome (multi-class classification). Evaluate with macro-F1. Majority baseline: 44.7% accuracy, 14.3% macro-F1.

**Task 2 — Exemption Classification**
Given narrative and decision text, identify which RTI Act exemptions were invoked (multi-label). Evaluate with micro-F1 and per-section F1.

**Task 3 — Compliance Outcome Prediction**
Given the original CIC directive and respondent's compliance submission, predict compliance outcome (SCN_DROPPED / SCN_CONTINUED / PENALTY_IMPOSED). Uses adjunct decision subset (n=17 in v1.0).

**Task 4 — Plain-Language Summarisation**
Given the full decision text, generate a citizen-accessible summary. Reference summaries available in Source A `response` field. Evaluate with ROUGE-L, BERTScore, and human faithfulness rubrics.

---

## Document Format Generations (Source B)

A notable finding is the evolution of CIC document templates:

- **Format 2023a** (n=111): `O R D E R / Facts / Decision:` headings; bilingual Hindi-English headers; party blocks on separate lines.
- **Format 2023b** (n=21): `Observations:` + `Decision:` sections; `Date of Decision` in header.
- **Format 2026** (n=166): `DECISION` all-caps block; explicit `INFORMATION COMMISSIONER: Name` label; inline party names; slash-separated dates.

---

## Data Collection and Extraction

**Source A:** Rule-based extraction from `jatinmehra/RTI-CASE-DATASET` using regex patterns for public authority, exemption sections, outcome language, penalty amounts, and final direction. Runs in ~30 seconds for 1,218 rows.

**Source B:** CIC decision PDFs collected from dsscic.nic.in (manual download with CAPTCHA). Text extracted using PyMuPDF. Format-aware rule-based extractors applied per document generation. Full pipeline runs in ~90 seconds for 298 PDFs. No LLM annotation used anywhere.

All scripts available at: [GitHub link — add after upload]

---

## Commissioners Represented (Source B)

| Commissioner | Count |
|---|---|
| Amita Pandove | 75 |
| Jaya Varma Sinha | 40 |
| Sudha Rani Relangi | 35 |
| Ashutosh Chaturvedi | 30 |
| Vanaja N. Sarna | 14 |

---

## Limitations

- 17.2% of primary cases carry `UNKNOWN` outcome labels (49% in CIC PDF subset), reflecting indirect Commission language not captured by current patterns; these require human review before use in supervised classification.
- CIC PDF corpus concentrated among 5 commissioners; may not represent the full diversity of Information Commission adjudication across India.
- Appellant name field has low coverage (<25%) due to format variation; not required for the four benchmark tasks.
- Does not include State Information Commission decisions.
- Exemption extraction relies on explicit section citations; implicit reasoning about exemptions is not captured.

---

## Ethical Considerations

All data is drawn from publicly available sources. CIC decisions are public records under Indian law. Personal names of appellants appear as part of the public record; researchers should apply appropriate de-identification for downstream applications involving sensitive matters.

Intended use: improving AI-assisted access to justice for Indian citizens. Not intended for use in discouraging legitimate RTI appeals.

---

## Citation

```bibtex
@dataset{bose2025rtibench,
  title     = {RTI-Bench: A Structured Dataset for Indian Right-to-Information Decision Analysis},
  author    = {Bose, Joy},
  year      = {2025},
  publisher = {HuggingFace},
  url       = {https://huggingface.co/datasets/joybose/rti-bench}
}
```

---

## License

CC BY 4.0. Source data from CIC portal is public domain under Indian government open data policy. Source A derived from `jatinmehra/RTI-CASE-DATASET` (original license applies to that subset).