Triple
T16026261
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GE Honda HF120 |
E388724
|
entity |
| Predicate | targetAircraftClass |
P1524
|
FINISHED |
| Object | twin-engine business jet |
—
|
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: twin-engine business jet | Statement: [GE Honda HF120, targetAircraftClass, twin-engine business jet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetAircraftClass Context triple: [GE Honda HF120, targetAircraftClass, twin-engine business jet]
-
A.
targetedAircraft
Indicates that one entity has selected or designated an aircraft as the object of an attack, tracking, or other directed action.
-
B.
aircraftType
chosen
Indicates the specific model or category of aircraft associated with an entity or event.
-
C.
intendedAircraft
Indicates that an aircraft is the one planned or designated to be used for a particular flight, mission, or operation.
-
D.
typeOfAviation
Indicates the specific category or kind of aviation to which an entity belongs (e.g., commercial, military, private).
-
E.
aircraftSpeedClass
Indicates the categorical speed range or performance class to which an aircraft’s speed belongs.
- 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_69d86dada3808190825d5f80d72fbe88 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1858a00888190b8505071575dc56f |
completed | April 17, 2026, 12:57 a.m. |
| PD | Predicate disambiguation | batch_69e1826a4f7c8190aba6d4f1075141b0 |
completed | April 17, 2026, 12:44 a.m. |
Created at: April 10, 2026, 4:56 a.m.