Triple
T25206719
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Virgin Blue |
E631271
|
entity |
| Predicate | operatedAircraftManufacturer |
P53350
|
FINISHED |
| Object | Boeing |
—
|
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: Boeing | Statement: [Virgin Blue, operatedAircraftManufacturer, Boeing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: operatedAircraftManufacturer Context triple: [Virgin Blue, operatedAircraftManufacturer, Boeing]
-
A.
wingManufacturer
Indicates that one entity is the manufacturer or producer of the wing component used by another entity.
-
B.
intendedAircraftManufacturer
Indicates that one entity is the manufacturer for which an aircraft (or aircraft model) is designed or planned, rather than necessarily the one that ultimately builds it.
-
C.
aircraftManufacturerOfAircraft
Indicates that a given manufacturer is the producer or builder of a specified aircraft.
-
D.
appliedToAircraftBuiltBy
Indicates that something (such as a regulation, modification, or action) is applied specifically to aircraft that were built by a particular manufacturer or builder.
-
E.
operatesAircraftBrand
chosen
Indicates that an entity actively uses or runs aircraft belonging to a specified brand in its operations.
- 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_69e75a8b86c4819089eda22c843b739f |
completed | April 21, 2026, 11:07 a.m. |
| NER | Named-entity recognition | batch_69f6d0d46aec819091edf97324d793ac |
completed | May 3, 2026, 4:36 a.m. |
| PD | Predicate disambiguation | batch_69f6cfe2183481908ae4e85a59c66f69 |
completed | May 3, 2026, 4:32 a.m. |
Created at: April 21, 2026, 12:52 p.m.