Triple
T2126757
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hope Creek Nuclear Generating Station |
E46443
|
entity |
| Predicate | hasCoolingTowers |
P35300
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Hope Creek Nuclear Generating Station, hasCoolingTowers, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCoolingTowers Context triple: [Hope Creek Nuclear Generating Station, hasCoolingTowers, yes]
-
A.
hasTurbines
Indicates that one entity is equipped with, contains, or includes one or more turbines in relation to another entity.
-
B.
coolingMethod
Indicates the technique or process used to remove heat from something or keep it at a lower temperature.
-
C.
powerplantType
Indicates the specific kind or category of power plant associated with an entity, based on how it generates energy.
-
D.
hasVentilationShafts
Indicates that one entity is equipped with or contains ventilation shafts that provide airflow or air passage.
-
E.
thermalPower
Indicates the amount of heat energy per unit time that a system, device, or process generates, transfers, or consumes.
- F. None of above. chosen
Provenance (4 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_69a88a1626548190ae59a5028c3baa8e |
completed | March 4, 2026, 7:37 p.m. |
| NER | Named-entity recognition | batch_69abbb59182081908470f9be97e272c8 |
completed | March 7, 2026, 5:44 a.m. |
| PD | Predicate disambiguation | batch_69abb7bd86cc8190938ef06c1ed6d969 |
completed | March 7, 2026, 5:29 a.m. |
| PDg | Predicate description generation | batch_69abb895d11881908345032595a679ba |
completed | March 7, 2026, 5:33 a.m. |
Created at: March 4, 2026, 7:44 p.m.