Datasets:

williamTLmiller
/

bva-decisions-structured-sample2019Present

license: cc-by-nc-4.0
language:
  - en
pretty_name: BVA Structured Decisions (2019–2025)
task_categories:
  - text-classification
  - token-classification
  - text-retrieval
  - question-answering
tags:
  - legal
  - law
  - legal-nlp
  - veterans-affairs
  - disability
  - bva
  - structured-extraction
  - administrative-law
size_categories:
  - 1K<n<10K

BVA Structured Decisions (2019–2025)

Structured, issue-level records extracted from U.S. Board of Veterans' Appeals (BVA) decisions — each decision parsed into its issues, conditions, outcomes, citations, and reasoning, with per-document provenance and completeness flags. Built for training and evaluating legal-AI models on veterans' disability adjudication.

This is a 2900-decision sample, balanced across seven years (2019–2025, decisions/year), so it's representative of the full corpus rather than skewed to one year. A larger full-corpus release and a commercial license are available (see Access & licensing below).

Honesty note (please read). Labels are silver (engine-produced, benchmarked against an LLM-labeled reference at ~96% outcome accuracy), not human-certified gold. Provenance and completeness ship with every row so you can verify and filter. See Quality & accuracy.

What's in it


Decisions	2900
Years	2019–2025 (balanced)
Format	CSV (one row per decision) — 23 columns
Coverage	99% of rows carry extracted issues and citations; 96% carry reasoning atoms
Source	Public BVA decisions published on va.gov

Outcome distribution (decision-level)

remanded · denied · granted · dismissed · reopened · withdrawn

Appeals regime

legacy · AMA · unknown (tagged from the decision text, not the year).

Conditions

107 distinct medical conditions. Top: back disability (490), knee disability (438), hearing loss (341), arthritis (302), psychiatric disorder (289), PTSD (287), peripheral neuropathy (272), sleep apnea (212), hypertension (195), foot disability (177).

Column dictionary

Column	Description
`doc_id`	BVA citation/docket number (the 2-digit prefix is the fiscal year).
`source_url`	Link to the original decision on va.gov for independent verification.
`schema`	Extraction schema used (`bva`).
`issues`	The appealed issues (pipe-separated).
`conditions` / `conditions_raw` / `conditions_detailed` / `condition_other`	Canonical condition tokens, raw phrasing, laterality/qualifiers, and an out-of-vocabulary flag.
`outcomes`	Decision-level dispositions (granted / denied / remanded / dismissed / reopened / withdrawn).
`outcome_by_issue`	Each issue tied to its own outcome (the core training unit).
`reasoning_by_issue`	Per-issue reasoning atoms (the "why").
`reasoning_completeness`	`full` / `partial` / `none` — quality tier for self-selecting a clean slice.
`reasoning_unfillable`	`True` when the source letter has no reasoning at all (so `none` is expected).
`regime` / `ama_docket`	Legacy vs. Appeals-Modernization-Act regime + AMA docket flag.
`citations`	Statutory/regulatory citations (38 U.S.C. / 38 C.F.R.), normalized and deduped.
`evidence`	Evidence types referenced (VA exam, private opinion, lay statement, etc.).
`reasoning_atoms`	Canonical reasoning findings (nexus established/not, benefit-of-doubt, duty-to-assist, etc.).
`judge_dates`	Decision date + Veterans Law Judge.
`signals_extracted` / `matrix_cells_used` / `avg_route_score` / `char_length`	Extraction telemetry + raw length.

Why it is useful

Issue-level supervision. outcome_by_issue and reasoning_by_issue link each appealed issue to its disposition and rationale — not just a document-level label.
Trainable + filterable. Completeness tiers let you train on the clean full slice or use everything; regime lets you separate legacy vs. AMA.
Verifiable. Every row carries a source_url back to the public original.
Representative. Balanced across 2019–2025, so temporal/longitudinal splits are honest.

Intended uses: training/evaluating models for claim-outcome prediction, issue and citation extraction, legal RAG over veterans' law, and fine-tuning assistants for BVA practice.

Quality & accuracy (read before you rely on it)

Silver, not gold. Records are produced by a deterministic extraction engine and benchmarked against an LLM-labeled reference at ~96% outcome-extraction accuracy (measured on 2019 issues). Human-verified gold validation is in progress and not yet reflected here.
What's well-covered: issues, conditions, outcomes, citations, and reasoning atoms (96–99% of rows populated).
Known limits: the none/partial reasoning rows are recoverable gaps, not curated blanks; regime is unknown for many rows where the text doesn't clearly signal it; condition extraction follows a controlled vocabulary (107 tokens) with an condition_other flag for the long tail.

Treat the accuracy figure as a silver benchmark, and verify against source_url for any high-stakes use.

“I can provide the full dataset (~350k decisions, 2019–2026) or targeted subsets such as:

• All PTSD / mental health cases • Back, knee, leg, hip, and orthopedic disabilities • TDIU and rating increase appeals • Herbicide/Gulf War presumptive claims • Hearing loss / tinnitus Each subset maintains the same structured format with reasoning atoms, per-issue outcomes, etc.”

Provenance, PII & ethics

Source: BVA decisions are U.S. federal records, published publicly on va.gov. The underlying text is public domain (17 U.S.C. §105); the structured layer (this dataset's value-add) is what the license below covers.
PII: BVA publishes decisions with appellants de-identified (referred to as "the Veteran"/initials). This release was screened with an automated PII gate (blocks SSN/phone/email/DOB/address). It may still contain incidental names (e.g., judges, place names) inherent to public legal text — review before any redistribution.
Not legal advice. This is research/ML data about adjudication patterns, not guidance for any individual claim.

Access & licensing

License: CC BY-NC 4.0 — free to use for research and non-commercial purposes, with attribution. The raw decision text is public domain; the NC term applies to the structured annotations in this dataset.
Commercial use / full corpus: the full multi-year corpus (and a commercial license) are available separately. Contact the maintainer to license it for commercial use.

Attribution

BVA Structured Decisions (2019–2025). Structured extraction of public Board of Veterans' Appeals decisions. Derived from va.gov public records; structured layer © the maintainer, released under CC BY-NC 4.0.

Changelog

v1 — 2900 decisions, balanced 2019–2025; 23-column document schema; silver labels (~96% benchmark).