Triple
T19637635
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | San Luis Valley Regional Airport |
E471440
|
entity |
| Predicate | hasAircraftMaintenance |
P71131
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [San Luis Valley Regional Airport, hasAircraftMaintenance, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAircraftMaintenance Context triple: [San Luis Valley Regional Airport, hasAircraftMaintenance, yes]
-
A.
hasMaintenance
chosen
Indicates that an entity is subject to, associated with, or requires a particular maintenance activity or maintenance record.
-
B.
aircraftTypeMaintained
Indicates that a maintenance entity performs or is responsible for maintaining a specific type of aircraft.
-
C.
hasMaintenanceService
Indicates that an entity receives or is covered by a maintenance service provided by another entity.
-
D.
isPartOfAviationSystem
Indicates that something functions as a component or subsystem within a broader aviation system or infrastructure.
-
E.
isAirworthy
Indicates that an aircraft or flying object meets the necessary safety and operational standards to be considered fit for flight.
- 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_69d8e511f28481909f4bc3ea9191e54a |
completed | April 10, 2026, 11:54 a.m. |
| NER | Named-entity recognition | batch_69e64107f3fc8190ace6ae67287d280c |
completed | April 20, 2026, 3:06 p.m. |
| PD | Predicate disambiguation | batch_69e514e5cb108190ae260e466c447314 |
completed | April 19, 2026, 5:46 p.m. |
Created at: April 10, 2026, 1:44 p.m.