Triple
T6210492
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Runway 06/24 |
E138854
|
entity |
| Predicate | isMainRunwayFor |
P8867
|
FINISHED |
| Object | international flights at José Martí 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: international flights at José Martí International Airport | Statement: [Runway 06/24, isMainRunwayFor, international flights at José Martí International Airport]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isMainRunwayFor Context triple: [Runway 06/24, isMainRunwayFor, international flights at José Martí International Airport]
-
A.
isPrimaryRunwayOf
chosen
Indicates that a runway serves as the main or principal runway for a particular airport or airfield.
-
B.
isRunwayOf
Indicates that a physical runway is a component or facility belonging to, used by, or officially associated with a particular airport or airfield.
-
C.
isSingleRunwayForAirport
Indicates that a runway is the only (single) runway serving a particular airport.
-
D.
runwayLength
Indicates the length of a runway associated with an airport or airfield.
-
E.
hasOppositeRunway
Indicates that one runway is paired with another runway that has the opposite or reciprocal orientation or designation.
- 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_69c008ada364819096c9e92c74d639b5 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c062896f3881909f264bb45badc5d0 |
completed | March 22, 2026, 9:43 p.m. |
| PD | Predicate disambiguation | batch_69c055fdea3c81908f5d910f0d36234a |
completed | March 22, 2026, 8:50 p.m. |
Created at: March 22, 2026, 4:21 p.m.