Triple
T1026825
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CH-148 Cyclone |
E22156
|
entity |
| Predicate | hasAvionics |
P21784
|
FINISHED |
| Object | advanced maritime mission system |
—
|
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: advanced maritime mission system | Statement: [CH-148 Cyclone, hasAvionics, advanced maritime mission system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAvionics Context triple: [CH-148 Cyclone, hasAvionics, advanced maritime mission system]
-
A.
avionics
Indicates that an entity is related to the electronic systems used to control, monitor, or assist the operation of aircraft or spacecraft.
-
B.
hasOnboardSystems
chosen
Indicates that an entity is equipped with or contains specific onboard systems or subsystems.
-
C.
airborneComponent
Indicates that one entity is a component or part of another entity specifically when that other entity is in an airborne state.
-
D.
usedInAviation
Indicates that something is employed or applied within the field or context of aviation.
-
E.
hasAircraftOnDisplay
Indicates that an entity exhibits or presents an aircraft as part of a display or collection.
- 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_69a493d6e380819097b384986ffc315c |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b95d35888190a20593a278175df7 |
completed | March 1, 2026, 10:10 p.m. |
| PD | Predicate disambiguation | batch_69a4b7276180819085c6b23501a6a6e0 |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:41 p.m.