Triple
T7018201
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | VOAT |
E162748
|
entity |
| Predicate | associatedAirportUse |
P58803
|
FINISHED |
| Object | public |
—
|
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 | Statement: [VOAT, associatedAirportUse, public]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedAirportUse Context triple: [VOAT, associatedAirportUse, public]
-
A.
airportUse
Indicates that an airport is used or utilized by a particular entity, such as an airline, organization, or service.
-
B.
associatedAirportServes
Indicates that a given airport provides service to, or is used by, the associated entity (such as a city, region, or facility).
-
C.
associatedAirport
chosen
Indicates a relationship where an entity is linked or connected to a specific airport, typically as its relevant or corresponding airport.
-
D.
airportSpecialization
Indicates that an airport is specialized or designated for a particular primary function, service type, or category of operations.
-
E.
associatedWithAirportType
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_69c6885a127c8190867b059bdccf13ff |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6e5ecd4488190bf19e42de55da98b |
completed | March 27, 2026, 8:17 p.m. |
| PD | Predicate disambiguation | batch_69c6e1b8118481909d76eb6616160e80 |
completed | March 27, 2026, 7:59 p.m. |
Created at: March 27, 2026, 2:34 p.m.