Triple
T12789476
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rogožarski |
E305718
|
entity |
| Predicate | aircraftCategoryProduced |
P106917
|
FINISHED |
| Object | biplanes |
—
|
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: biplanes | Statement: [Rogožarski, aircraftCategoryProduced, biplanes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: aircraftCategoryProduced Context triple: [Rogožarski, aircraftCategoryProduced, biplanes]
-
A.
aircraftConfigurationProduced
Indicates that a specific aircraft configuration has been manufactured or produced.
-
B.
appliedToAircraftBuiltBy
Indicates that something (such as a regulation, modification, or action) is applied specifically to aircraft that were built by a particular manufacturer or builder.
-
C.
typicalAircraftTypeCategory
Indicates the general class or category of aircraft type that is most commonly associated with or used in a given context.
-
D.
appliedToAircraftDesignedBy
Indicates that something (such as a component, system, or regulation) is applied to an aircraft that was designed by a specified designer or organization.
-
E.
developedAircraft
Indicates that an entity (such as a person or organization) was responsible for designing, creating, or engineering a particular 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_69d7bdf366888190a8cccb982606889c |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96e6a61f48190972e241e70bc392c |
completed | April 10, 2026, 9:40 p.m. |
| PD | Predicate disambiguation | batch_69d9640ba0688190973e4e7ec8d4a8e0 |
completed | April 10, 2026, 8:56 p.m. |
| PDg | Predicate description generation | batch_69d96d87078c819083ea724238992204 |
completed | April 10, 2026, 9:37 p.m. |
Created at: April 9, 2026, 5:30 p.m.