Triple
T18794891
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ZGSZ |
E459605
|
entity |
| Predicate | hasTerminal |
P182
|
FINISHED |
| Object | Terminal 3 |
—
|
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: Terminal 3 | Statement: [ZGSZ, hasTerminal, Terminal 3]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Terminal 3 Context triple: [ZGSZ, hasTerminal, Terminal 3]
-
A.
Terminal 3
Terminal 3 is one of the main passenger terminals at Phoenix Sky Harbor International Airport, serving as a hub for multiple domestic and some international flights with modernized facilities and amenities.
-
B.
Terminal 3
Terminal 3 is a major domestic passenger terminal at San Francisco International Airport, primarily serving United Airlines and its partners.
-
C.
Terminal 3
Terminal 3 is one of the passenger terminals at Adolfo Suárez Madrid–Barajas Airport in Madrid, Spain, serving as part of the airport’s main complex for domestic and international flights.
-
D.
Terminal 3
chosen
Terminal 3 is a major passenger terminal facility at Guangzhou Baiyun International Airport, serving as one of its primary hubs for domestic and international air travel.
-
E.
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.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8d396f54c8190ba49db31e8743842 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5a01dbb308190bbbbd5a18e26451e |
completed | April 20, 2026, 3:40 a.m. |
Created at: April 10, 2026, 11:53 a.m.