Triple
T35871450
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | J 32B fighter variant |
E1037235
|
entity |
| Predicate | hasOriginAircraft |
P89695
|
FINISHED |
| Object | Saab 32 Lansen |
—
|
NE NERFINISHED |
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: Saab 32 Lansen | Statement: [J 32B fighter variant, hasOriginAircraft, Saab 32 Lansen]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOriginAircraft Context triple: [J 32B fighter variant, hasOriginAircraft, Saab 32 Lansen]
-
A.
usedAircraftOrigin
Indicates the place or source from which a used aircraft was originally obtained or came.
-
B.
hasOriginAirport
Indicates that something, typically a flight or journey, departs from or is associated with a specific origin airport.
-
C.
hasBasedAircraft
Indicates that an aircraft is regularly stationed or primarily based at a particular location or facility.
-
D.
basedOnAircraft
chosen
Indicates that one entity is derived from, modeled after, or otherwise uses a particular aircraft as its basis or primary reference.
-
E.
hasTypicalOriginAirport
Indicates that an entity, such as a flight route or airline service, is commonly or usually associated with a particular origin airport from which it typically departs.
- 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_69f76e1e701c8190a4990d4978ce4fe6 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fed6da0390819096b88ef4714b144e |
completed | May 9, 2026, 6:40 a.m. |
| PD | Predicate disambiguation | batch_69fed53517d081909966f31707625f1a |
completed | May 9, 2026, 6:33 a.m. |
Created at: May 3, 2026, 4:06 p.m.