Triple
T32722018
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | One-Eleven short-haul jet |
E836697
|
entity |
| Predicate | powerplantPosition |
P182274
|
FINISHED |
| Object | aft fuselage |
—
|
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: aft fuselage | Statement: [One-Eleven short-haul jet, powerplantPosition, aft fuselage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: powerplantPosition Context triple: [One-Eleven short-haul jet, powerplantPosition, aft fuselage]
-
A.
powerplantLocation
Indicates that a power plant is situated at or associated with a specific geographic location.
-
B.
powerplantFor
Indicates that one entity functions as the power plant or primary energy source serving another entity.
-
C.
powerplant
Indicates that an entity functions as a facility or installation where energy sources are converted into usable power, typically electricity.
-
D.
powerplantPower
Indicates that a power plant provides or generates a specified amount of electrical power.
-
E.
powerPlantName
Indicates the specific name assigned to a power plant.
- 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_69f34935455881909088975d79460418 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f7886be6d8819095ec62e4f2cee858 |
completed | May 3, 2026, 5:39 p.m. |
| PD | Predicate disambiguation | batch_69f7841440f48190b4346c08855951d2 |
completed | May 3, 2026, 5:21 p.m. |
| PDg | Predicate description generation | batch_69f7886b27f08190ab4580f949222c93 |
completed | May 3, 2026, 5:39 p.m. |
Created at: May 1, 2026, 1:11 a.m.