Triple
T14269829
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | KWI |
E353749
|
entity |
| Predicate | hasPassengerTerminal |
P1297
|
FINISHED |
| Object | Terminal 3 |
E415027
|
NE 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: Terminal 3 | Statement: [KWI, hasPassengerTerminal, Terminal 3]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Terminal 3 Context triple: [KWI, hasPassengerTerminal, Terminal 3]
-
A.
Terminal 3
Terminal 3 is the main international passenger terminal at José Martí International Airport in Havana, Cuba, handling most long-haul and major airline operations.
-
B.
Terminal 3
Terminal 3 is one of the passenger terminals at Stockholm Arlanda Airport, serving regional and short-haul flights within the airport’s overall terminal complex.
-
C.
Terminal 3
chosen
Terminal 3 is one of the passenger terminals at Perth Airport in Western Australia, serving domestic airline operations and related airport services.
-
D.
Terminal 3
Terminal 3 is a major passenger terminal at Xi'an Xianyang International Airport, serving as one of its primary facilities for domestic and international flights.
-
E.
Terminal 3
Terminal 3 is a passenger terminal at Clark International Airport (RPLL) in the Philippines, serving commercial airline operations and traveler services.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d8278d25148190abf1a8c8f5f533ad |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de657fe6708190b41de48c43cff647 |
completed | April 14, 2026, 4:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd324f501081908f7017302bc40b3a |
completed | May 8, 2026, 12:46 a.m. |
Created at: April 10, 2026, 1:10 a.m.