Triple
T1256306
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Operation Barkhane |
E12399
|
entity |
| Predicate | airAssetsUsed |
P6269
|
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: [Operation Barkhane, airAssetsUsed, fighter aircraft]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: airAssetsUsed Context triple: [Operation Barkhane, airAssetsUsed, fighter aircraft]
-
A.
carrierAircraft
Indicates that an aircraft is designed, equipped, or used to operate from an aircraft carrier.
-
B.
fleetIncludes
Indicates that a particular fleet contains or is composed of the specified entity or entities as its members.
-
C.
usedOnAircraftName
Indicates that something is employed or applied on an aircraft identified by a specific name.
-
D.
airSupport
chosen
Indicates that one entity provides aerial assistance or backing to another, typically through aircraft-based protection, transport, or attack.
-
E.
aircraftManufacturerUsed
Indicates that a particular aircraft manufacturer was employed or utilized in relation to another entity, such as for production, design, or supply purposes.
- 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_69a4933352e08190ac617291985e76c0 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4bfa726548190911b4022dc1be3c3 |
completed | March 1, 2026, 10:37 p.m. |
| PD | Predicate disambiguation | batch_69a4bb6c977c8190a2bf3e8b67a59beb |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:50 p.m.