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rti-bench

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Text Classification
Summarization
Question Answering
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Tags:
legal
india
rti
right-to-information
administrative-law
nlp
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metadata 
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 

@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).