Triple
T35017184
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aero Vodochody |
E1010083
|
entity |
| Predicate | L-29DelfinRole |
P159104
|
FINISHED |
| Object | jet trainer |
—
|
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: jet trainer | Statement: [Aero Vodochody, L-29DelfinRole, jet trainer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: L-29DelfinRole Context triple: [Aero Vodochody, L-29DelfinRole, jet trainer]
-
A.
aircraftRoleDesignedFor
chosen
Indicates that an aircraft is specifically designed or intended to perform a particular role or function.
-
B.
aircraftRoleDesigned
Indicates that an aircraft was specifically designed to fulfill a particular operational role or function.
-
C.
aircraftRoleOfDesignatedAircraft
Indicates that an aircraft has the specified operational role or function as a designated aircraft within a particular context or mission.
-
D.
notableAircraftRole
Indicates that an aircraft is notably associated with performing a particular role or function.
-
E.
fighterType
Indicates the specific combat or fighting style category that an entity belongs to.
- 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_69f76dcc3ac8819096a3ed52f5fa2523 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f7858aa5508190a07dde993b3356fc |
completed | May 3, 2026, 5:27 p.m. |
| PD | Predicate disambiguation | batch_69f7841812f081909d878955d114088e |
completed | May 3, 2026, 5:21 p.m. |
Created at: May 3, 2026, 4:01 p.m.