Triple
T26115809
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Finningley |
E658821
|
entity |
| Predicate | hasHistoricUseNearby |
P51359
|
FINISHED |
| Object | Royal Air Force station |
—
|
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: Royal Air Force station | Statement: [Finningley, hasHistoricUseNearby, Royal Air Force station]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHistoricUseNearby Context triple: [Finningley, hasHistoricUseNearby, Royal Air Force station]
-
A.
hasFormerUseNearby
chosen
Indicates that something in the vicinity previously had a particular use or function that is no longer current.
-
B.
hasHistoricalUsageIn
Indicates that something has been used or practiced within a particular historical period, context, or tradition.
-
C.
hasNearbyHistoricArea
Indicates that one entity is located close to another entity that is designated as a historic area.
-
D.
hasFormerUse
Indicates that something previously served a particular function or role that it no longer has.
-
E.
hasFormerNearbyLandmark
Indicates that an entity previously had a nearby landmark that no longer exists or no longer holds the same status or relevance.
- 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_69f7117e55908190a67105e92bc4830f |
completed | May 3, 2026, 9:12 a.m. |
| PD | Predicate disambiguation | batch_69f70f380690819090cc34763ba460ed |
completed | May 3, 2026, 9:02 a.m. |
Created at: April 26, 2026, 8:05 p.m.