Triple
T20643179
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hannover Airport |
E507281
|
entity |
| Predicate | hasPassengerTerminal |
P1297
|
FINISHED |
| Object | Terminal B |
—
|
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 B | Statement: [Hannover Airport, hasPassengerTerminal, Terminal B]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Terminal B Context triple: [Hannover Airport, hasPassengerTerminal, Terminal B]
-
A.
Terminal B
Terminal B is one of the passenger terminals at Vnukovo International Airport in Moscow, serving as a key facility for handling flights and travelers.
-
B.
Terminal B
Terminal B is a passenger terminal at Volgograd International Airport in Russia, serving as one of the airport’s main facilities for handling flights and travelers.
-
C.
Terminal B
Terminal B was a former passenger terminal at Shenzhen Bao’an International Airport that has since been decommissioned and demolished as part of the airport’s modernization and expansion.
-
D.
Terminal B
chosen
Terminal B is one of the passenger terminals at Hannover Airport in Germany, serving airline operations and traveler services.
-
E.
Terminal B
Terminal B is one of the passenger terminals at Düsseldorf Airport (DUS), serving various domestic and international flights with check-in, security, and boarding facilities.
- 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_69e0b4be702c8190a3d2410a881d310a |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6af1c51f48190abba54a5aace9fc8 |
completed | April 20, 2026, 10:56 p.m. |
Created at: April 16, 2026, 11:43 a.m.