Triple
T10288593
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RJOY |
E241300
|
entity |
| Predicate | hasICAOCodeForSameAirport |
P419
|
FINISHED |
| Object | RJOY |
—
|
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: RJOY | Statement: [RJOY, hasICAOCodeForSameAirport, RJOY]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasICAOCodeForSameAirport Context triple: [RJOY, hasICAOCodeForSameAirport, RJOY]
-
A.
ICAOcode
chosen
Indicates that an entity is identified by a specific four-letter airport or aerodrome code assigned by the International Civil Aviation Organization (ICAO).
-
B.
successorCodeForSameAirport
Indicates that one code is the direct replacement or follow-up code for the same airport, reflecting a change while the underlying airport remains the same.
-
C.
airportAlsoKnownAs
Indicates that an airport is referred to by an alternative name or alias in addition to its primary name.
-
D.
hasIATAcode
Indicates that an entity, typically a transportation facility like an airport, is associated with a specific IATA (International Air Transport Association) code.
-
E.
hasAirportCodeCity
Indicates that a city is associated with a specific airport code (such as an IATA or ICAO code) that identifies its 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_69d381aaafc08190af475ef58dc16aba |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d7ccb7ec8190a538cf279e48116e |
completed | April 7, 2026, 10:09 a.m. |
| PD | Predicate disambiguation | batch_69d4d1f117708190928f92ae2611d724 |
completed | April 7, 2026, 9:44 a.m. |
Created at: April 6, 2026, 11:41 a.m.