Triple
T26115814
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Finningley |
E658821
|
entity |
| Predicate | hasFormerNameOfNearbyAirport |
P149492
|
FINISHED |
| Object | Robin Hood Airport Doncaster Sheffield |
—
|
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: Robin Hood Airport Doncaster Sheffield | Statement: [Finningley, hasFormerNameOfNearbyAirport, Robin Hood Airport Doncaster Sheffield]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFormerNameOfNearbyAirport Context triple: [Finningley, hasFormerNameOfNearbyAirport, Robin Hood Airport Doncaster Sheffield]
-
A.
hasFormerNearbyAirportName
chosen
Indicates that an entity previously had a nearby airport known by a different name than its current nearby airport name.
-
B.
hasFormerAirport
Indicates that an entity previously had an airport that is no longer in operation or no longer exists.
-
C.
previousAirportName
Indicates the name that an airport was known by before its current name.
-
D.
namedAfterAirportOriginalName
Indicates that one entity is named after the original name of an airport, rather than its current or later name.
-
E.
namedAfterAirport
Indicates that one entity has been given a name derived from or in honor of a specific 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_69ee5bc20298819099a42be042eb2349 |
completed | April 26, 2026, 6:38 p.m. |
| NER | Named-entity recognition | batch_69f68805b4848190b75da14996d52a38 |
completed | May 2, 2026, 11:25 p.m. |
| PD | Predicate disambiguation | batch_69f68609c0b08190a8e1238a4d97c270 |
completed | May 2, 2026, 11:17 p.m. |
Created at: April 26, 2026, 8:05 p.m.