Triple
T9224058
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | McDonnell Douglas T-45 Goshawk |
E221634
|
entity |
| Predicate | T-45A |
P1524
|
FINISHED |
| Object | analog cockpit 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: analog cockpit version | Statement: [McDonnell Douglas T-45 Goshawk, T-45A, analog cockpit version]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: T-45A Context triple: [McDonnell Douglas T-45 Goshawk, T-45A, analog cockpit version]
-
A.
aircraftMaritimePatrol
Indicates that an aircraft is engaged in maritime patrol operations, monitoring and surveying sea areas for security, reconnaissance, or search-and-rescue purposes.
-
B.
specificCarrierAircraftVariant
Indicates that one aircraft variant is a specific version designed or adapted for carrier-based operations of another, more general aircraft variant.
-
C.
isHelicopterOf
Indicates that one entity is a helicopter that belongs to, is operated by, or is otherwise associated with another entity.
-
D.
squadronFlagshipOf
Indicates that one entity serves as the primary or lead flagship vessel of a particular squadron.
-
E.
aircraftType
chosen
Indicates the specific model or category of aircraft associated with an entity or event.
- 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_69ca83ec8db08190a9110df8232885d2 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccda9c71c4819089dcc3689f322529 |
completed | April 1, 2026, 8:43 a.m. |
| PD | Predicate disambiguation | batch_69cc7a3daeb481908b0abde3fbc1f1f0 |
completed | April 1, 2026, 1:51 a.m. |
Created at: March 30, 2026, 7:28 p.m.