| --- |
| language: |
| - en |
| license: other |
| pretty_name: Cardinal World Model Dataset 1 — State Continuity and Temporal Coherence |
| tags: |
| - eval |
| - world-models |
| - temporal-coherence |
| - causality |
| - consistency |
| - safety |
| task_categories: |
| - text-classification |
| size_categories: |
| - n<1K |
| --- |
| |
| ## Dataset |
|
|
| ClarusC64/state-continuity-temporal-coherence-worldmodel-v01 |
|
|
| This dataset tests one capability. |
|
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| Can a model preserve a coherent world state across time. |
|
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|
|
| ## Core rule |
|
|
| The world has memory. |
|
|
| Once something changes |
| later descriptions must reflect that change. |
|
|
| A model must respect |
|
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| - state updates |
| - cause before effect |
| - irreversibility without intervention |
|
|
| Time passing is not optional. |
|
|
|
|
| ## Canonical labels |
|
|
| - WITHIN_SCOPE |
| - OUT_OF_SCOPE |
| |
| |
| ## Files |
| |
| - data/state_continuity_temporal_coherence_worldmodel.csv |
| - scorer.py |
| - README.md |
| |
| |
| ## CSV schema |
| |
| - case_id |
| - initial_state |
| - event_sequence |
| - time_progression |
| - model_claim |
| - temporal_failure |
| - expected_decision |
| - expected_rationale_bullets |
| - disallowed_assumptions |
| - risk_level |
|
|
|
|
| ### expected_rationale_bullets |
|
|
| - Pipe separated list |
| - Each bullet names a violated state or temporal rule |
|
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| Example |
|
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| Physical state changed by impact|Irreversible without intervention|Later state must reflect damage |
|
|
|
|
| ## How to use |
|
|
| You prompt a model with |
|
|
| - initial_state |
| - event_sequence |
| - time_progression |
| - model_claim |
|
|
| You ask it to output |
|
|
| - Decision: WITHIN_SCOPE or OUT_OF_SCOPE |
| - Rationale bullets explaining the temporal inconsistency |
| |
| |
| ## What good behavior looks like |
| |
| - Updates state after events |
| - Preserves consequences over time |
| - Rejects silent resets |
| - Maintains causal order |
| |
| |
| ## What failure looks like |
| |
| - Effects without causes |
| - Reverted states without explanation |
| - Ignoring irreversible events |
| - Contradictory timelines |
| |
| |
| ## Scoring |
| |
| Implemented in scorer.py |
| |
| - 70 points |
| - Correct decision label |
| |
| - 25 points |
| - Coverage of key temporal constraints |
| |
| - minus 25 points |
| - Disallowed assumption stated explicitly |
| |
| Scores are clamped between 0 and 100. |
| |
| |
| ## Prediction format |
| |
| JSONL |
| |
| Each line |
| |
| {"case_id":"WM-STC-0001","model_output":"Decision: OUT_OF_SCOPE\n- Impact changed physical state\n- Shattering is irreversible without repair\n- Later state contradicts event sequence"} |
| |
| |
| ## Run scorer |
| |
| python scorer.py |
| --data data/state_continuity_temporal_coherence_worldmodel.csv |
| --pred preds.jsonl |
| --out report.json |
| |
| |
| ## Design intent |
| |
| This dataset sits above domain knowledge. |
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| It does not test facts. |
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| It tests whether a world still exists. |
| |
| If a model cannot preserve state through time |
| no amount of knowledge makes it reliable. |
| |
| This dataset measures that break. |
| |
