Triple
T20553206
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bishop of Doncaster |
E504648
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object | Doncaster |
—
|
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: Doncaster | Statement: [Bishop of Doncaster, namedAfter, Doncaster]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Doncaster Context triple: [Bishop of Doncaster, namedAfter, Doncaster]
-
A.
Doncaster
chosen
Doncaster is a large town and metropolitan borough in South Yorkshire, England, known historically for its railway heritage, horse racing, and role as a regional commercial center.
-
B.
Yorkton
Yorkton is a small city in southeastern Saskatchewan, Canada, known as a regional hub for agriculture and services.
-
C.
Scunthorpe
Scunthorpe is an industrial town in North Lincolnshire, England, historically known for its steel production.
-
D.
Wakefield
Wakefield is a 2016 drama film starring Bryan Cranston as a successful lawyer who abruptly abandons his life to secretly observe his family from hiding, exploring themes of identity, isolation, and self-discovery.
-
E.
Wakefield
Wakefield is a historic cathedral city in West Yorkshire, Northern England, known for its medieval heritage and role as an administrative and commercial center in the region.
- 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_69e0b4b52c048190952b4d0f430813a3 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6a5db052c8190801e53f6148113c8 |
completed | April 20, 2026, 10:16 p.m. |
Created at: April 16, 2026, 11:38 a.m.