Triple
T11815297
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | YSSY |
E280983
|
entity |
| Predicate | associatedAirportRunwaySurfaceType |
P422
|
FINISHED |
| Object | asphalt |
—
|
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: asphalt | Statement: [YSSY, associatedAirportRunwaySurfaceType, asphalt]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedAirportRunwaySurfaceType Context triple: [YSSY, associatedAirportRunwaySurfaceType, asphalt]
-
A.
runwaySurface
chosen
Indicates the type or condition of the surface material that a runway is made of or covered with.
-
B.
isPrimaryRunwayOf
Indicates that a runway serves as the main or principal runway for a particular airport or airfield.
-
C.
runwayCharacteristic
Indicates a relationship where specific attributes or features are associated with a runway.
-
D.
hasRunwayType
Indicates that an airport or airfield has a runway of a specified type or surface classification.
-
E.
runwayUsage
Indicates that a particular runway is being used or assigned for aircraft operations such as takeoffs or landings.
- 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_69d6ab26aae88190b2489efcb2a24234 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a658f918819092c2db05fe2ab0ce |
completed | April 10, 2026, 7:27 a.m. |
| PD | Predicate disambiguation | batch_69d8a24e9a088190aff7932d1ff93dbf |
completed | April 10, 2026, 7:10 a.m. |
Created at: April 8, 2026, 9:42 p.m.