Triple
T4331955
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Glasgow–Barra beach landing route |
E96772
|
entity |
| Predicate | operatesToAirportType |
P54051
|
FINISHED |
| Object | beach airport |
—
|
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: beach airport | Statement: [Glasgow–Barra beach landing route, operatesToAirportType, beach airport]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: operatesToAirportType Context triple: [Glasgow–Barra beach landing route, operatesToAirportType, beach airport]
-
A.
servesAirportType
chosen
Indicates that a transportation service or facility provides service to, or is designated for, a specific type or category of airport.
-
B.
operatesAirport
Indicates that one entity manages and runs the operations of an airport.
-
C.
appliesToAirport
Indicates that something is relevant, valid, or specifically intended for use at a particular airport.
-
D.
hasAircraftOperationsType
Indicates the specific category or type of aircraft operations associated with an entity, such as commercial, military, or private use.
-
E.
operatesFlightsTo
Indicates that one entity (typically an airline) runs or provides flight services to the location represented by the other entity.
- 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_69b34542fd908190b11b08faad8decfd |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3514dc588819086a4c6d585c1b5b1 |
completed | March 12, 2026, 11:50 p.m. |
| PD | Predicate disambiguation | batch_69b34f4e13fc8190a42c519f37959d27 |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:13 p.m.