Phase 4 Detailed Plan: Validation, Benchmarking, and Final Reporting
Timeline target: Month 4
Goal
Validate the prototype against defined metrics, benchmark performance, document findings, and deliver final report artifacts.
Scope
In scope:
- Test execution on real and synthetic datasets.
- Benchmarking against phase-defined metrics.
- Error analysis and refinement loop.
- Final documentation and roadmap.
Out of scope:
- Enterprise production rollout.
- Full ecosystem-level implementation.
- Integrated Phase 3 prototype.
- Synthetic and public/real evaluation datasets.
- Benchmark definitions and acceptance thresholds.
The current Phase 4 MVP validates existing Phase 3 artifacts and compares one-or-more runs without retraining.
Primary command:
PYTHONPATH=src python scripts/run_phase4_validation.py \
--baseline-dir artifacts/phase-3-freeze \
--comparison-dirs artifacts/phase-3-nb artifacts/phase-3-logreg artifacts/phase-3-privacybert \
--output-dir artifacts/phase-4
Equivalent package command:
prert-phase4 \
--baseline-dir artifacts/phase-3-freeze \
--comparison-dirs artifacts/phase-3-nb artifacts/phase-3-logreg artifacts/phase-3-privacybert \
--output-dir artifacts/phase-4
MVP outputs:
artifacts/phase-4/phase4_validation_report.jsonartifacts/phase-4/phase4_validation_report.mdartifacts/phase-4/phase4_leaderboard.jsonl
Supervisor-facing GUI workflow:
PYTHONPATH=src python scripts/run_phase4_web.py --port 8501
The GUI allows uploads for:
- company privacy policy documents
- database schema files
and returns an evidence-backed compliance score with detected risks.
Notes:
--require-bayesian upgrades Bayesian evidence checks from advisory to required.--strict exits with status code 2 when baseline required checks fail.
Steps to Complete
- Build validation test plan
- Define scenario matrix:
- normal operations,
- high-risk policy clauses,
- missing/incomplete data,
- conflicting indicator evidence.
- Define success thresholds for each scenario.
- Execute benchmark suite
- Run batch benchmarks on all scenarios.
- Capture classification and risk-scoring metrics with confidence intervals.
- Perform robustness and sensitivity analysis
- Perturb key inputs and observe score stability.
- Test model behavior under class imbalance and sparse evidence.
- Conduct error analysis
- Identify top failure modes in clause classification and score estimation.
- Trace errors back to data, mapping, or model assumptions.
- Refine prototype where justified
- Apply targeted fixes only when they improve benchmark outcomes and interpretability.
- Re-run impacted benchmarks and log deltas.
- Finalize reporting package
- Prepare validation summary.
- Prepare benchmark report.
- Prepare final report with limitations and future roadmap.
- Completion and handoff
- Ensure all artifacts are versioned and reproducible.
- Conduct final review and sign-off.
Deliverables
- Benchmark report with scenario-level results.
- Validation summary with risk/limitation analysis.
- Final report and roadmap.
- Packaged validated prototype.
Recommended Acceptance Checks
- Benchmarks executed for all predefined scenarios.
- Results include both performance and uncertainty metrics.
- Known limitations and assumptions are explicitly documented.
- Final report is reproducible from versioned artifacts.
Risks and Mitigations
- Risk: Benchmark definitions are too vague.
- Mitigation: Lock thresholds before large test execution.
- Risk: Last-minute model changes invalidate comparisons.
- Mitigation: Freeze baseline and track all post-freeze deltas.
- Risk: Report quality suffers due to time compression.
- Mitigation: Start report skeleton in Week 1 and update continuously.
Recommended Week-by-Week Breakdown
Week 1:
- Finalize test plan and benchmark scripts.
Week 2:
- Execute full benchmark suite and collect outputs.
Week 3:
- Perform error analysis and targeted refinements.
Week 4:
- Finalize reports, artifacts, and sign-off package.
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