Triple
T30866386
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Runway 12/30 |
E786211
|
entity |
| Predicate | ownershipTypeOfAirport |
P169557
|
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: [Runway 12/30, ownershipTypeOfAirport, public]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ownershipTypeOfAirport Context triple: [Runway 12/30, ownershipTypeOfAirport, public]
-
A.
airportOwnershipModel
chosen
Indicates the type or structure of ownership or governance arrangement under which an airport is held or operated.
-
B.
airlineOwnershipType
Indicates the type or nature of ownership relationship that exists between an airline and its owning entity.
-
C.
airportOwner
Indicates that one entity owns, controls, or holds primary legal responsibility for an airport.
-
D.
ownershipType
Indicates the specific nature or category of the ownership relationship that one entity holds over another.
-
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_69f224b9df2c819086f55f8bcf7f382e |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f6df450014819099d118e5c2d697fa |
completed | May 3, 2026, 5:38 a.m. |
| PD | Predicate disambiguation | batch_69f6de07836481908785cde9c511920b |
completed | May 3, 2026, 5:32 a.m. |
Created at: April 29, 2026, 8:47 p.m.