Triple
T9804769
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SF.260TP |
E237926
|
entity |
| Predicate | originatesFromAircraft |
P89695
|
FINISHED |
| Object | SF.260 piston-engined version |
—
|
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: SF.260 piston-engined version | Statement: [SF.260TP, originatesFromAircraft, SF.260 piston-engined version]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originatesFromAircraft Context triple: [SF.260TP, originatesFromAircraft, SF.260 piston-engined version]
-
A.
usedAircraftOrigin
Indicates the place or source from which a used aircraft was originally obtained or came.
-
B.
basedOnAircraft
chosen
Indicates that one entity is derived from, modeled after, or otherwise uses a particular aircraft as its basis or primary reference.
-
C.
embarkedAircraft
Indicates that one entity boarded or got onto an aircraft as a passenger or occupant.
-
D.
locationOnAircraft
Indicates that one entity is physically situated on or within an aircraft.
-
E.
aircraftOriginCountry
Indicates the country from which an aircraft originates, such as where it was built, registered, or primarily associated.
- 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_69ca84dd4608819097ff4ed00feca280 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdab7a0ce881908f0555d194dece3f |
completed | April 1, 2026, 11:34 p.m. |
| PD | Predicate disambiguation | batch_69cd03dd2da881909052fbf29736a773 |
completed | April 1, 2026, 11:39 a.m. |
Created at: March 30, 2026, 8:29 p.m.