Triple
T25940532
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Málaga–Costa del Sol Airport |
E653683
|
entity |
| Predicate | has focus city airline |
P120244
|
FINISHED |
| Object | easyJet |
—
|
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: easyJet | Statement: [Málaga–Costa del Sol Airport, has focus city airline, easyJet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: has focus city airline Context triple: [Málaga–Costa del Sol Airport, has focus city airline, easyJet]
-
A.
hasFocusCityAirline
Indicates that an airline designates a particular city as one of its focus cities, where it concentrates a significant portion of its operations without it necessarily being a primary hub.
-
B.
associatedAirportFocusCityFor
chosen
Indicates that an airport serves as a designated focus city for a particular airline or carrier.
-
C.
airlineHub
Indicates that a particular location (typically an airport or city) serves as a central hub or primary operational base for an airline.
-
D.
airlineBaseCity
Indicates the city that serves as the primary operational base or headquarters location for an airline.
-
E.
mainAirlineFocus
Indicates that an airline is the primary or central focus of attention, operations, or analysis in a given context.
- 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_69f5afec3e94819080d9ba86cf8c866e |
completed | May 2, 2026, 8:03 a.m. |
Created at: April 22, 2026, 8:40 a.m.