Triple
T1421273
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lanzarote Airport |
E30228
|
entity |
| Predicate | hasPassengerTerminalFor |
P1297
|
FINISHED |
| Object | low-cost airlines |
—
|
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: low-cost airlines | Statement: [Lanzarote Airport, hasPassengerTerminalFor, low-cost airlines]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPassengerTerminalFor Context triple: [Lanzarote Airport, hasPassengerTerminalFor, low-cost airlines]
-
A.
hasPassengerTerminal
chosen
Indicates that one entity possesses or is equipped with a passenger terminal used for boarding, alighting, or handling passengers.
-
B.
hasPassengerTerminalDesign
Indicates a design relationship in which one entity specifies or defines the passenger terminal layout, structure, or configuration of another entity.
-
C.
hasBusStation
Indicates that a place or area contains or is served by a bus station.
-
D.
hasCargoTerminal
Indicates that a location or facility includes or is equipped with a cargo terminal for handling freight.
-
E.
hasTransportHub
Indicates that a location contains or serves as a central facility where multiple transport routes or modes connect for passenger or cargo movement.
- 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_69a498fb823c8190a67ce4c4837e641a |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c42210948190a8fb5e3f9ee3213b |
completed | March 1, 2026, 10:56 p.m. |
| PD | Predicate disambiguation | batch_69a4bf0d64c08190ac12977b86fbe4ab |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 8 p.m.