Triple
T23397390
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Allegheny County Airport |
E559396
|
entity |
| Predicate | wasPrimaryAirportUntil |
P81616
|
FINISHED |
| Object | 1952 |
—
|
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: 1952 | Statement: [Allegheny County Airport, wasPrimaryAirportUntil, 1952]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wasPrimaryAirportUntil Context triple: [Allegheny County Airport, wasPrimaryAirportUntil, 1952]
-
A.
replacedAsMainAirportFor
Indicates that one airport has taken over the role of being the primary or main airport serving a particular area from another airport.
-
B.
hasFormerNearbyAirportName
Indicates that an entity previously had a nearby airport known by a different name than its current nearby airport name.
-
C.
hasPrimaryAirportRole
Indicates that an entity holds the main or principal functional role associated with an airport.
-
D.
previousPrimaryAirportFor
chosen
Indicates that one airport was formerly the main or primary airport serving a particular location or entity before being replaced by another.
-
E.
hasFormerAirport
Indicates that an entity previously had an airport that is no longer in operation or no longer exists.
- 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_69e24549610c8190a069d6411ce5f661 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1a4dd05cc81908c1e91974ffccf21 |
completed | April 29, 2026, 6:27 a.m. |
| PD | Predicate disambiguation | batch_69f061dde2e481908308952f9c0d3c2e |
completed | April 28, 2026, 7:29 a.m. |
Created at: April 17, 2026, 5:37 p.m.