Triple
T22537719
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yakutsk Airport |
E557199
|
entity |
| Predicate | parkingApron |
P40806
|
FINISHED |
| Object | available for passenger aircraft |
—
|
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: available for passenger aircraft | Statement: [Yakutsk Airport, parkingApron, available for passenger aircraft]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: parkingApron Context triple: [Yakutsk Airport, parkingApron, available for passenger aircraft]
-
A.
hasParkingApron
chosen
Indicates that a location or facility includes a designated parking apron area for vehicles or aircraft.
-
B.
parkingStructure
Indicates that one entity is a parking facility or structure associated with another entity (such as a building, location, or organization).
-
C.
parkSection
Indicates a relationship where a specific area or subsection belongs to, is contained within, or is designated as part of a larger park.
-
D.
parkingType
Indicates the specific kind or category of parking arrangement associated with an entity (e.g., street, garage, lot, reserved).
-
E.
parkEntranceArea
Indicates the area that serves as an entrance or access point to a park.
- 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_69e11e57483c8190b0887c4f8ff26446 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15f2f671c8190b7a7d9b6d0d64a9b |
completed | April 29, 2026, 1:30 a.m. |
| PD | Predicate disambiguation | batch_69e898c864148190a3f5feec7967d49c |
completed | April 22, 2026, 9:45 a.m. |
Created at: April 16, 2026, 8:51 p.m.