Triple
T5207678
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | English Electric Lightning |
E117550
|
entity |
| Predicate | fuelConsumption |
P62021
|
FINISHED |
| Object | high |
—
|
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: high | Statement: [English Electric Lightning, fuelConsumption, high]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fuelConsumption Context triple: [English Electric Lightning, fuelConsumption, high]
-
A.
fuelEfficiency
Indicates how effectively an entity uses fuel to perform a given amount of work or travel a certain distance.
-
B.
typicalFuel
Indicates the kind of fuel that is normally or most commonly used by an entity (such as a device, vehicle, or system).
-
C.
fuelFraction
Indicates the proportion of an object's total mass or capacity that consists of fuel.
-
D.
fuelEffect
Indicates the influence or impact that a given fuel has on a process, system, or outcome.
-
E.
fuelRole
Indicates that one entity serves as the fuel or energy source used or consumed by another entity in a process or operation.
- 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_69bd4463dd3c81909966123f20b79d57 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7a6d70d081908c74e86b3bca9ba2 |
completed | March 20, 2026, 4:48 p.m. |
| PD | Predicate disambiguation | batch_69bd77bb4e8c819094b5ac7cf61512f9 |
completed | March 20, 2026, 4:37 p.m. |
| PDg | Predicate description generation | batch_69bd79000cf88190b3c05d95395b0cd2 |
completed | March 20, 2026, 4:42 p.m. |
Created at: March 20, 2026, 1:47 p.m.