Triple
T16282047
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Runway 8/26 |
E395288
|
entity |
| Predicate | isNumberOfRunwaysAtAirport |
P19671
|
FINISHED |
| Object | one of the primary runways at Phoenix Sky Harbor International Airport |
—
|
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: one of the primary runways at Phoenix Sky Harbor International Airport | Statement: [Runway 8/26, isNumberOfRunwaysAtAirport, one of the primary runways at Phoenix Sky Harbor International Airport]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isNumberOfRunwaysAtAirport Context triple: [Runway 8/26, isNumberOfRunwaysAtAirport, one of the primary runways at Phoenix Sky Harbor International Airport]
-
A.
numberOfRunways
Indicates the quantity of runways associated with a given entity, such as an airport or airfield.
-
B.
isSingleRunwayForAirport
Indicates that a runway is the only (single) runway serving a particular airport.
-
C.
hasRunwayCount
chosen
Indicates the number of runways that a given entity (such as an airport) possesses.
-
D.
isPrimaryRunwayOf
Indicates that a runway serves as the main or principal runway for a particular airport or airfield.
-
E.
hasNumberOfPassengerTerminalsAtAirport
Indicates the relationship that specifies how many passenger terminals are present at a given 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_69d87f22c7248190a54c949738441e2e |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e24910c6b881909ae5cc0908dd8eb2 |
completed | April 17, 2026, 2:52 p.m. |
| PD | Predicate disambiguation | batch_69e219f68d308190b71c1601303f0628 |
completed | April 17, 2026, 11:31 a.m. |
Created at: April 10, 2026, 5:05 a.m.