Triple
T9804688
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SIAI-Marchetti |
E237924
|
entity |
| Predicate | aircraftRoleSpecialization |
P90066
|
FINISHED |
| Object | trainer 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: trainer aircraft | Statement: [SIAI-Marchetti, aircraftRoleSpecialization, trainer aircraft]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: aircraftRoleSpecialization Context triple: [SIAI-Marchetti, aircraftRoleSpecialization, trainer aircraft]
-
A.
aircraftRoleSupported
Indicates that a given role or function is supported or enabled for a particular aircraft.
-
B.
notableAircraftRole
Indicates that an aircraft is notably associated with performing a particular role or function.
-
C.
primaryAircraftRole
Indicates the main operational function or mission type an aircraft is primarily designed or used to perform.
-
D.
basedAircraftRole
Indicates that an aircraft is regularly stationed at a particular location in a specified operational role or function.
-
E.
usedOnAircraftRole
Indicates that something is employed or applied in the context of a specific role or function on an aircraft.
- 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_69ca84dd4608819097ff4ed00feca280 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdab7a0ce881908f0555d194dece3f |
completed | April 1, 2026, 11:34 p.m. |
| PD | Predicate disambiguation | batch_69cd03dd2da881909052fbf29736a773 |
completed | April 1, 2026, 11:39 a.m. |
| PDg | Predicate description generation | batch_69cd06abc9248190a506b64e9c516d03 |
completed | April 1, 2026, 11:51 a.m. |
Created at: March 30, 2026, 8:29 p.m.