Triple
T16794856
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Morava Airport |
E408205
|
entity |
| Predicate | roleForAirSerbia |
P89878
|
FINISHED |
| Object | secondary operational base |
—
|
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: secondary operational base | Statement: [Morava Airport, roleForAirSerbia, secondary operational base]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleForAirSerbia Context triple: [Morava Airport, roleForAirSerbia, secondary operational base]
-
A.
usedByAirlineRole
chosen
Indicates that something (such as a resource, system, or process) is utilized by a specific role or position within an airline organization.
-
B.
airlineAllianceRole
Indicates the specific role or function an airline holds within an airline alliance.
-
C.
businessRoleOfSidLuft
Indicates that the subject holds or held a business-related role or position in relation to Sid Luft.
-
D.
airportLineRole
Indicates the specific functional role or responsibility an entity has in relation to an airport transit line or route.
-
E.
airlineContext
Indicates a relationship, situation, or action that specifically occurs within or is constrained by an airline-related context (such as flights, carriers, or air travel operations).
- 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_69d88393905081908d00a86b99996ac8 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3b2a96d888190a9876c3784bb7f95 |
completed | April 18, 2026, 4:34 p.m. |
| PD | Predicate disambiguation | batch_69e319cf691c819083e39225f5777ef0 |
completed | April 18, 2026, 5:42 a.m. |
Created at: April 10, 2026, 5:22 a.m.