Triple
T7891176
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Juancho E. Yrausquin Airport |
E183236
|
entity |
| Predicate | hasRunwayWidth |
P26238
|
FINISHED |
| Object | approximately 18 metres |
—
|
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: approximately 18 metres | Statement: [Juancho E. Yrausquin Airport, hasRunwayWidth, approximately 18 metres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRunwayWidth Context triple: [Juancho E. Yrausquin Airport, hasRunwayWidth, approximately 18 metres]
-
A.
hasRunwayType
Indicates that an airport or airfield has a runway of a specified type or surface classification.
-
B.
runwayWidth
chosen
Indicates the measured width of a runway as a spatial dimension.
-
C.
hasRunwayLengthCategory
Indicates that an airport or airfield is associated with a specific categorical range of runway lengths (e.g., short, medium, long).
-
D.
hasRunwaySide
Indicates that a runway is located on or associated with a particular side or boundary of another feature (such as an airport or airfield area).
-
E.
hasRunwayPresence
Indicates that an entity maintains a physical runway or landing strip suitable for aircraft operations.
- 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_69ca828c474c8190a254d6499871eaff |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb39ee137081908e87e35016c3a176 |
completed | March 31, 2026, 3:05 a.m. |
| PD | Predicate disambiguation | batch_69cae92b0cd881908e715a10d3252e83 |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 5 p.m.