Triple
T17270105
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gateacre |
E419232
|
entity |
| Predicate | hasNeighbourhood |
P4813
|
FINISHED |
| Object | Woolton |
E796697
|
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: Woolton | Statement: [Gateacre, hasNeighbourhood, Woolton]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Woolton Context triple: [Gateacre, hasNeighbourhood, Woolton]
-
A.
Woolton
chosen
Woolton is a suburban district of Liverpool, England, known for its historic village character and associations with The Beatles.
-
B.
Wolverton
Wolverton is a historic railway town in Buckinghamshire, England, now part of the Milton Keynes urban area.
-
C.
Woolston
Woolston is a riverside suburb of Christchurch, New Zealand, known historically for its industrial activity and proximity to the Heathcote River.
-
D.
Woolston
Woolston is a district of Southampton in Hampshire, England, historically known for its shipbuilding and marine engineering industries.
-
E.
Woolverton
Woolverton is a surname most notably associated with American screenwriter and playwright Linda Woolverton, known for her work on major Disney films.
- 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_69d886da626481908a14ce7830329a35 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42f4917ec819096356ad2ed24d51d |
completed | April 19, 2026, 1:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01794a09b8819086da30f38c6d4c20 |
completed | May 11, 2026, 6:38 a.m. |
Created at: April 10, 2026, 5:40 a.m.