Triple
T7634527
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RAF Leconfield |
E172839
|
entity |
| Predicate | nearbyCity |
P350
|
FINISHED |
| Object | Beverley |
E406105
|
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: Beverley | Statement: [RAF Leconfield, nearbyCity, Beverley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Beverley Context triple: [RAF Leconfield, nearbyCity, Beverley]
-
A.
Beverley
chosen
Beverley is a historic market town and civil parish in the East Riding of Yorkshire, England, known for its impressive Gothic minster and medieval architecture.
-
B.
Yorkton
Yorkton is a small city in southeastern Saskatchewan, Canada, known as a regional hub for agriculture and services.
-
C.
Bakewell
Bakewell is a historic market town in Derbyshire, England, famed for its traditional Bakewell pudding and its picturesque setting in the Peak District.
-
D.
Northbourne
Northbourne is a small village and civil parish in Kent, England, known for its rural character and historic church.
-
E.
Banwell
Banwell is a village and civil parish in North Somerset, England, known for its historic caves and medieval architecture.
- 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_69c69952849881908fdcea7a93bfc307 |
completed | March 27, 2026, 2:50 p.m. |
| NER | Named-entity recognition | batch_69c6faa83fcc8190a3f0bb20cbe1b2d6 |
completed | March 27, 2026, 9:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c870be4e18819089781c7493dea13b |
completed | March 29, 2026, 12:22 a.m. |
Created at: March 27, 2026, 3:57 p.m.