Triple
T13063854
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stelio Frati |
E329267
|
entity |
| Predicate | aircraftUsedFor |
P64999
|
FINISHED |
| Object | training |
—
|
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: training | Statement: [Stelio Frati, aircraftUsedFor, training]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: aircraftUsedFor Context triple: [Stelio Frati, aircraftUsedFor, training]
-
A.
aircraftTypesUsedOn
Indicates the types or models of aircraft that are used on or assigned to a particular route, service, operation, or context.
-
B.
referredAircraftUsedFor
chosen
Indicates that the referenced aircraft is utilized for a particular purpose, role, or operation in relation to another entity or context.
-
C.
referredAircraftUsedIn
Indicates that an aircraft being referred to is the one that was actually used in a particular event, operation, or context.
-
D.
aircraftUsedFromFleetOf
Indicates that a specific aircraft is selected and used from a particular fleet of aircraft.
-
E.
usedOnAircraftName
Indicates that something is employed or applied on an aircraft identified by a specific name.
- 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_69d80771749c81909a6d9197b9504872 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d980e9bdfc81908eb90fb50597df64 |
completed | April 10, 2026, 10:59 p.m. |
| PD | Predicate disambiguation | batch_69d9803d46688190bac6b7d208f08d01 |
completed | April 10, 2026, 10:57 p.m. |
Created at: April 9, 2026, 8:59 p.m.