Triple
T702830
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | WNF (Austria) |
E14034
|
entity |
| Predicate | aircraftRoleProduced |
P2860
|
FINISHED |
| Object | fighter aircraft |
—
|
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: fighter aircraft | Statement: [WNF (Austria), aircraftRoleProduced, fighter aircraft]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: aircraftRoleProduced Context triple: [WNF (Austria), aircraftRoleProduced, fighter aircraft]
-
A.
primaryAircraftRole
chosen
Indicates the main operational function or mission type an aircraft is primarily designed or used to perform.
-
B.
usedOnAircraftName
Indicates that something is employed or applied on an aircraft identified by a specific name.
-
C.
aircraftManufacturerUsed
Indicates that a particular aircraft manufacturer was employed or utilized in relation to another entity, such as for production, design, or supply purposes.
-
D.
aircraftType
Indicates the specific model or category of aircraft associated with an entity or event.
-
E.
launchedAircraftIn
Indicates that an entity initiated the takeoff or deployment of an aircraft within a specified location or context.
- 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_69a493494ec48190ae6751683625a9ba |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a58d4c3c8190ad4527d14bca5e6e |
completed | March 1, 2026, 8:46 p.m. |
| PD | Predicate disambiguation | batch_69a4a4edc33881909a978268f6dd5d82 |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:36 p.m.