Triple
T22616142
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Susanna Beverley |
E558151
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Beverley |
—
|
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: Beverley | Statement: [Susanna Beverley, familyName, Beverley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Beverley Context triple: [Susanna Beverley, familyName, 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.
Beverley
Beverley is a small rural town in Western Australia known for its agricultural community and historic country character.
-
C.
Beckingham
Beckingham is a village and civil parish in the Bassetlaw district of Nottinghamshire, England.
-
D.
Bewley
Bewley is an English-language surname borne by various notable individuals across fields such as acting, sports, and public service.
-
E.
Yorkton
Yorkton is a small city in southeastern Saskatchewan, Canada, known as a regional hub for agriculture and services.
- 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_69e24545a8e08190bfa7482a2c725ff1 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f167edec2481909c2f06607b3cb8f6 |
completed | April 29, 2026, 2:07 a.m. |
Created at: April 17, 2026, 2:59 p.m.