Triple
T1681744
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ministro Pistarini International Airport |
E36352
|
entity |
| Predicate | hasCargoTrafficType |
P32692
|
FINISHED |
| Object | air cargo |
—
|
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: air cargo | Statement: [Ministro Pistarini International Airport, hasCargoTrafficType, air cargo]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCargoTrafficType Context triple: [Ministro Pistarini International Airport, hasCargoTrafficType, air cargo]
-
A.
servesPassengerTrafficType
Indicates that a transportation facility or service accommodates a specified type or category of passenger traffic.
-
B.
hasCargoAirline
Indicates that one entity operates as a cargo airline for, or provides cargo air transport services to, another entity.
-
C.
hasTruckTraffic
Indicates that there is truck-related vehicular movement or flow occurring on or through a specified location or route.
-
D.
hasAircraftOperationsType
Indicates the specific category or type of aircraft operations associated with an entity, such as commercial, military, or private use.
-
E.
hasTrafficPattern
Indicates that there is a characteristic or recurring flow of traffic associated with an entity, such as its typical volume, direction, or timing of movement.
- 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_69a886139ed081909af0940aa9313512 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aba644070c81908745b56d981fe273 |
completed | March 7, 2026, 4:15 a.m. |
| PD | Predicate disambiguation | batch_69aa61b57a6881909373af287ef24799 |
completed | March 6, 2026, 5:10 a.m. |
| PDg | Predicate description generation | batch_69aba641e6a881909645577e72b53df2 |
completed | March 7, 2026, 4:14 a.m. |
Created at: March 4, 2026, 7:29 p.m.