Triple
T36914703
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | EGPD |
E913012
|
entity |
| Predicate | associatedAirportHasCargoFacilities |
P2420
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [EGPD, associatedAirportHasCargoFacilities, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedAirportHasCargoFacilities Context triple: [EGPD, associatedAirportHasCargoFacilities, true]
-
A.
isCargoAirportCode
Indicates that an airport code specifically designates an airport primarily used for cargo operations.
-
B.
hasAirportRelatedFunction
Indicates that something performs a role, service, or activity specifically related to the operation, support, or functioning of an airport.
-
C.
hasCargoAirline
Indicates that one entity operates as a cargo airline for, or provides cargo air transport services to, another entity.
-
D.
hasCargoTerminal
chosen
Indicates that a location or facility includes or is equipped with a cargo terminal for handling freight.
-
E.
hasCargoHandlingSpecialization
Indicates that an entity is specialized in handling specific types of cargo or cargo-handling 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_69f76e879768819085c2fb31a6a5b44b |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a037c8e2c648190a65fc9c7872861af |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a10036481909c71188b2a0e7f04 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:13 p.m.