Triple
T23659945
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miami Executive Airport |
E584415
|
entity |
| Predicate | runway9L/27RLength |
P6291
|
FINISHED |
| Object | 6000 feet (approximate) |
—
|
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: 6000 feet (approximate) | Statement: [Miami Executive Airport, runway9L/27RLength, 6000 feet (approximate)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: runway9L/27RLength Context triple: [Miami Executive Airport, runway9L/27RLength, 6000 feet (approximate)]
-
A.
runwayLength
chosen
Indicates the length of a runway associated with an airport or airfield.
-
B.
runwayWidth
Indicates the measured width of a runway as a spatial dimension.
-
C.
runwayLengthUnit
Indicates the unit of measurement used to express the length of a runway in the relationship.
-
D.
runwayCharacteristic
Indicates a relationship where specific attributes or features are associated with a runway.
-
E.
runwayInformationAvailableIn
Indicates that information about a runway is available within or through a specified medium, source, or context.
- 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_69e248ffc0888190ae23c4731eb8b7ac |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b35f03448190834991c2a65ef0e4 |
completed | April 29, 2026, 7:29 a.m. |
| PD | Predicate disambiguation | batch_69f118d7903c8190bb590a71771e93af |
completed | April 28, 2026, 8:30 p.m. |
Created at: April 17, 2026, 6:50 p.m.