Triple
T25940512
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Málaga–Costa del Sol Airport |
E653683
|
entity |
| Predicate | is main airport for |
P151946
|
FINISHED |
| Object | Costa del Sol |
—
|
NE NERFINISHED |
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: Costa del Sol | Statement: [Málaga–Costa del Sol Airport, is main airport for, Costa del Sol]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: is main airport for Context triple: [Málaga–Costa del Sol Airport, is main airport for, Costa del Sol]
-
A.
isMainAirportStopFor
Indicates that a given airport serves as the primary or principal stop for a specified route, service, or transportation connection.
-
B.
mainAccessAirport
chosen
Indicates that one location serves as the primary airport providing access to another place or region.
-
C.
hasPrimaryAirportRole
Indicates that an entity holds the main or principal functional role associated with an airport.
-
D.
isOnlyInternationalAirportOf
Indicates that an airport is the single, unique international airport serving a particular city, region, or country.
-
E.
servesAsPrimaryAirportOperatorForCity
Indicates that an entity functions as the main organization responsible for operating the primary airport serving a particular city.
- 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_69e7ab3fd2f881908837305e4ba98011 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f6045dedb4819087530b823c036d51 |
completed | May 2, 2026, 2:04 p.m. |
| PD | Predicate disambiguation | batch_69f4a10480748190a2e67bd399fc435d |
completed | May 1, 2026, 12:48 p.m. |
Created at: April 22, 2026, 8:40 a.m.