Triple
T38693408
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sydney Airport International Terminal |
E949930
|
entity |
| Predicate | isTerminalOfAirportWithICAOCode |
P155924
|
FINISHED |
| Object | YSSY |
—
|
NE NERFINISHED |
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: YSSY | Statement: [Sydney Airport International Terminal, isTerminalOfAirportWithICAOCode, YSSY]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isTerminalOfAirportWithICAOCode Context triple: [Sydney Airport International Terminal, isTerminalOfAirportWithICAOCode, YSSY]
-
A.
isCivilAirport
Indicates that an airport is designated and used primarily for civilian (non-military) aviation operations.
-
B.
terminusAAirport
Indicates that an airport serves as the terminal (end) point for a specified air route or service.
-
C.
isMainAirportStopFor
Indicates that a given airport serves as the primary or principal stop for a specified route, service, or transportation connection.
-
D.
hasIcaoAirport
chosen
Indicates that an entity is associated with an airport identified by a specific ICAO (International Civil Aviation Organization) airport code.
-
E.
isCargoAirportCode
Indicates that an airport code specifically designates an airport primarily used for cargo 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_69f76f0124408190bb39c3040734846b |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fcdfbc71c481908ba7f87907b17782 |
completed | May 7, 2026, 6:53 p.m. |
| PD | Predicate disambiguation | batch_69fcdbe580b8819087f143596b2c79c0 |
completed | May 7, 2026, 6:37 p.m. |
Created at: May 3, 2026, 4:33 p.m.