Triple
T20761610
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Cube |
E510987
|
entity |
| Predicate | energyEffectOnHumans |
P19730
|
FINISHED |
| Object | dangerous and unstable |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: dangerous and unstable | Statement: [The Cube, energyEffectOnHumans, dangerous and unstable]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: energyEffectOnHumans Context triple: [The Cube, energyEffectOnHumans, dangerous and unstable]
-
A.
impactOnHumans
Indicates a relationship where something produces an effect, influence, or consequence on humans.
-
B.
humanImpact
Indicates the effect or influence that human activities have on another entity, system, or environment.
-
C.
humanImpactLevel
Indicates the degree or extent to which human activities affect or influence a given entity, system, or environment.
-
D.
pollutionHealthEffect
Indicates the impact that a given source or level of pollution has on the health or well-being of affected entities.
-
E.
healthEffect
chosen
Indicates the impact or consequence that one entity has on the health or well-being of another.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69e0b4c909ec8190b05987f1639513f6 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c2493a188190a336a35ea134e5f7 |
completed | April 21, 2026, 12:18 a.m. |
| PD | Predicate disambiguation | batch_69e5c0509608819080cdbf47fcddfe36 |
completed | April 20, 2026, 5:57 a.m. |
Created at: April 16, 2026, 12:35 p.m.