Triple
T13972918
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wolverton |
E336108
|
entity |
| Predicate | hasNeighbourhood |
P4813
|
FINISHED |
| Object | Old Wolverton |
E336108
|
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: Old Wolverton | Statement: [Wolverton, hasNeighbourhood, Old Wolverton]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Old Wolverton Context triple: [Wolverton, hasNeighbourhood, Old Wolverton]
-
A.
Wolverton
chosen
Wolverton is a historic railway town in Buckinghamshire, England, now part of the Milton Keynes urban area.
-
B.
Woolverton
Woolverton is a surname most notably associated with American screenwriter and playwright Linda Woolverton, known for her work on major Disney films.
-
C.
Woolston
Woolston is a district of Southampton in Hampshire, England, historically known for its shipbuilding and marine engineering industries.
-
D.
Wellesbourne
Wellesbourne is a large English village in Warwickshire, known for its historic airfield and proximity to Stratford-upon-Avon.
-
E.
Wolterton
Wolterton is an English country estate and civil parish in Norfolk, best known as the setting of the historic Wolterton Hall.
- 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_69d81c61f3508190aaf2ca0dc0002c59 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2e8fd6d48190a157eae8df3a2f3a |
completed | April 14, 2026, 12:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fba1df334c8190a3d65198cc3d11f6 |
completed | May 6, 2026, 8:17 p.m. |
Created at: April 9, 2026, 10:18 p.m.