Triple
T10755847
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | KLGC |
E253691
|
entity |
| Predicate | appliesToAirportType |
P16113
|
FINISHED |
| Object | public-use 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: public-use airport | Statement: [KLGC, appliesToAirportType, public-use airport]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appliesToAirportType Context triple: [KLGC, appliesToAirportType, public-use airport]
-
A.
appliesToAirport
Indicates that something is relevant, valid, or specifically intended for use at a particular airport.
-
B.
servesAirportType
Indicates that a transportation service or facility provides service to, or is designated for, a specific type or category of airport.
-
C.
isLocatedAtAirportType
Indicates that one entity is situated at, or associated with, an airport of a specified type (e.g., international, regional, military).
-
D.
airportTypePresent
Indicates that a specific type or category of airport is present or exists in relation to the referenced entity.
-
E.
associatedWithAirportType
chosen
Indicates that an entity has a connection or linkage to a specific category or type of airport.
- 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_69d6aa5f54f4819082d0bbcb6f8797e6 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d72e9e224c819099d16aba77322812 |
completed | April 9, 2026, 4:44 a.m. |
| PD | Predicate disambiguation | batch_69d6f311529c819080ca5493d55d6050 |
completed | April 9, 2026, 12:30 a.m. |
Created at: April 8, 2026, 9:15 p.m.