Triple
T29876558
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Airbus Helicopters H160 |
E758748
|
entity |
| Predicate | fuelEfficiencyFeature |
P27882
|
FINISHED |
| Object | Safran Arrano engines |
—
|
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: Safran Arrano engines | Statement: [Airbus Helicopters H160, fuelEfficiencyFeature, Safran Arrano engines]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fuelEfficiencyFeature Context triple: [Airbus Helicopters H160, fuelEfficiencyFeature, Safran Arrano engines]
-
A.
fuelEfficiency
Indicates how effectively an entity uses fuel to perform a given amount of work or travel a certain distance.
-
B.
energyEfficiencyFeature
chosen
Indicates that an entity has a design, technology, or characteristic specifically intended to reduce energy consumption or improve energy performance.
-
C.
fuelConsumption
Indicates the amount of fuel used by an entity (such as a vehicle or device) over a specified distance, time, or operation.
-
D.
fuelSystemFeature
Indicates that there is a specific characteristic, component, or functional aspect associated with a fuel system.
-
E.
fuelCharacteristic
Indicates a relationship where a fuel is associated with one of its defining properties or qualities, such as composition, performance, or behavior.
- 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_69f2245d0d7081909e37ee328542bcd7 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f676ca352c819087f6d085ab531b03 |
completed | May 2, 2026, 10:12 p.m. |
| PD | Predicate disambiguation | batch_69f66ac32b60819092290b2de35988d3 |
completed | May 2, 2026, 9:21 p.m. |
Created at: April 29, 2026, 5:56 p.m.