Triple
T10109232
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kiev-class aircraft carrier |
E218197
|
entity |
| Predicate | aircraftOperationType |
P92236
|
FINISHED |
| Object | STOVL |
—
|
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: STOVL | Statement: [Kiev-class aircraft carrier, aircraftOperationType, STOVL]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: aircraftOperationType Context triple: [Kiev-class aircraft carrier, aircraftOperationType, STOVL]
-
A.
hasAircraftOperationsType
Indicates the specific category or type of aircraft operations associated with an entity, such as commercial, military, or private use.
-
B.
airlineOperationsType
Indicates the type or category of operational activities an airline conducts (e.g., passenger, cargo, charter, or mixed services).
-
C.
aircraftRoleOperated
Indicates that an entity operates or has operated in a specified role or function within the context of aircraft operations.
-
D.
aircraftType
Indicates the specific model or category of aircraft associated with an entity or event.
-
E.
typeOfAviation
Indicates the specific category or kind of aviation to which an entity belongs (e.g., commercial, military, private).
- F. None of above. chosen
Provenance (4 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_69ca83da93fc8190b54e44bc2b34857c |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cdd0cbd8a48190b2af6177d1249f58 |
completed | April 2, 2026, 2:13 a.m. |
| PD | Predicate disambiguation | batch_69cd4b9ed7e48190aa132ef8a69b49f9 |
completed | April 1, 2026, 4:45 p.m. |
| PDg | Predicate description generation | batch_69cd4f8f869c8190a82ad040993e0244 |
completed | April 1, 2026, 5:02 p.m. |
Created at: March 30, 2026, 9:03 p.m.