Triple
T28288754
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gerlach–Empire Airport |
E713360
|
entity |
| Predicate | runway 7/25 width (meters) |
P26238
|
FINISHED |
| Object | 24 |
—
|
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: 24 | Statement: [Gerlach–Empire Airport, runway 7/25 width (meters), 24]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: runway 7/25 width (meters) Context triple: [Gerlach–Empire Airport, runway 7/25 width (meters), 24]
-
A.
runwayWidth
chosen
Indicates the measured width of a runway as a spatial dimension.
-
B.
runwayLength
Indicates the length of a runway associated with an airport or airfield.
-
C.
runway
Indicates a relationship where a runway serves as the takeoff and landing surface used by aircraft at an airport or airfield.
-
D.
runwayInformationAvailableIn
Indicates that information about a runway is available within or through a specified medium, source, or context.
-
E.
runwayCharacteristic
Indicates a relationship where specific attributes or features are associated with a runway.
- 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_69efb52371d88190a1381c4e58a3b731 |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_69f6afebd7ec8190ab696f363d84abf0 |
completed | May 3, 2026, 2:16 a.m. |
| PD | Predicate disambiguation | batch_69f6aca204148190850a3dc325bc07b7 |
completed | May 3, 2026, 2:02 a.m. |
Created at: April 27, 2026, 11:28 p.m.