Triple
T11815306
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | YSSY |
E280983
|
entity |
| Predicate | associatedAirportCountryCode |
P34624
|
FINISHED |
| Object | AU |
—
|
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: AU | Statement: [YSSY, associatedAirportCountryCode, AU]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedAirportCountryCode Context triple: [YSSY, associatedAirportCountryCode, AU]
-
A.
airportLocationCountry
chosen
Indicates that an airport is geographically situated within a specific country.
-
B.
associatedAirportCountrySubdivision
Indicates the specific country subdivision (such as a state, province, or region) in which the associated airport is located.
-
C.
linkedAirlineCountry
Indicates that there is an association between an airline and a country, such as the country where the airline is based, registered, or primarily operates.
-
D.
associatedWithAirportCode
Indicates that one entity has a relationship or connection to an airport identified by a specific airport code.
-
E.
associatedAirport
Indicates a relationship where an entity is linked or connected to a specific airport, typically as its relevant or corresponding airport.
- 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.