Triple
T35017189
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aero Vodochody |
E1010083
|
entity |
| Predicate | L-39NGRole |
P159104
|
FINISHED |
| Object | next-generation 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: next-generation jet trainer | Statement: [Aero Vodochody, L-39NGRole, next-generation jet trainer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: L-39NGRole Context triple: [Aero Vodochody, L-39NGRole, next-generation jet trainer]
-
A.
L-159ALCARole
Indicates that an entity plays the specific role labeled "L-159ALCA" in relation to another entity or context.
-
B.
aircraftTrainedOn
Indicates that an aircraft has been used as the platform or subject for training a person or crew in its operation or related skills.
-
C.
hasFixedWingTrainingRole
Indicates that an entity serves in a training capacity specifically related to the operation or use of fixed-wing aircraft.
-
D.
fighterType
Indicates the specific combat or fighting style category that an entity belongs to.
-
E.
aircraftRoleDesignedFor
chosen
Indicates that an aircraft is specifically designed or intended to perform a particular role or function.
- 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_69f78ce78b508190955848e133398dc8 |
completed | May 3, 2026, 5:59 p.m. |
| PD | Predicate disambiguation | batch_69f78b8f4cc08190b49fccd798cb25d7 |
completed | May 3, 2026, 5:53 p.m. |
Created at: May 3, 2026, 4:01 p.m.