Triple
T21407529
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ragley Hall |
E528077
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Alcester |
—
|
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: Alcester | Statement: [Ragley Hall, locatedNear, Alcester]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alcester Context triple: [Ragley Hall, locatedNear, Alcester]
-
A.
Alcester
chosen
Alcester is a historic market town in Warwickshire, England, known for its Roman heritage and traditional timber-framed buildings.
-
B.
Tewkesbury
Tewkesbury is a historic market town in England known for its well-preserved medieval streets, timber-framed buildings, and the prominent Tewkesbury Abbey.
-
C.
Tewkesbury
Tewkesbury is a rural locality in the north-west of Tasmania, Australia, situated inland from the coastal city of Burnie.
-
D.
Shrewsbury
Shrewsbury is a historic market town in Shropshire, England, known for its well-preserved medieval streets and timber-framed buildings.
-
E.
Shrewsbury
Shrewsbury is a small rural town in Rutland County, Vermont, known for its scenic Green Mountain landscapes and tight-knit community.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b520ee3c8190abddbee7e37e834c |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e8b1b1acd881908556981ed788340c |
completed | April 22, 2026, 11:32 a.m. |
Created at: April 16, 2026, 5:32 p.m.