Triple
T10985023
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pratt & Whitney J58 |
E259605
|
entity |
| Predicate | coolingUseOfFuel |
P10369
|
FINISHED |
| Object | lubricant cooling |
—
|
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: lubricant cooling | Statement: [Pratt & Whitney J58, coolingUseOfFuel, lubricant cooling]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coolingUseOfFuel Context triple: [Pratt & Whitney J58, coolingUseOfFuel, lubricant cooling]
-
A.
coolingRequirement
Indicates that an entity requires or is subject to a specific amount or type of cooling to operate within acceptable conditions.
-
B.
hasCoolingFlow
Indicates that an entity is equipped with or utilizes a system or mechanism to remove heat or maintain a lower temperature through the flow of a cooling medium.
-
C.
coolant
chosen
Indicates that one entity functions as a coolant for another, serving to absorb and remove heat from it.
-
D.
coolingLossCause
Indicates that one entity is the cause or source of another entity’s loss of cooling.
-
E.
fuelCycleFeature
Indicates a characteristic, attribute, or aspect associated with a nuclear fuel cycle process or stage.
- 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_69d6aa895f4c8190887a15460ef622f4 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d772ed1eb88190b7333b746f76a088 |
completed | April 9, 2026, 9:35 a.m. |
| PD | Predicate disambiguation | batch_69d72e9055908190b438f039574aaaaf |
completed | April 9, 2026, 4:44 a.m. |
Created at: April 8, 2026, 9:24 p.m.