Triple
T2126758
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hope Creek Nuclear Generating Station |
E46443
|
entity |
| Predicate | hasCoolingTowerType |
P35301
|
FINISHED |
| Object | natural draft cooling tower |
—
|
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: natural draft cooling tower | Statement: [Hope Creek Nuclear Generating Station, hasCoolingTowerType, natural draft cooling tower]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCoolingTowerType Context triple: [Hope Creek Nuclear Generating Station, hasCoolingTowerType, natural draft cooling tower]
-
A.
coolingMethod
Indicates the technique or process used to remove heat from something or keep it at a lower temperature.
-
B.
turbineType
Indicates the specific kind or category of turbine associated with or used by an entity.
-
C.
furnaceType
Indicates the specific kind or category of furnace associated with an entity.
-
D.
powerplantType
Indicates the specific kind or category of power plant associated with an entity, based on how it generates energy.
-
E.
hasTowerHeight
Indicates that an entity (such as a tower or structure) has a specific height value associated with it.
- 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.