Triple
T15013109
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Duke of Brunswick-Bevern |
E377887
|
entity |
| Predicate | capital |
P234
|
FINISHED |
| Object | Bevern |
E370549
|
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: Bevern | Statement: [Duke of Brunswick-Bevern, capital, Bevern]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bevern Context triple: [Duke of Brunswick-Bevern, capital, Bevern]
-
A.
Bevern
chosen
Bevern is a municipality in Lower Saxony, Germany, historically associated with the ducal House of Brunswick-Bevern.
-
B.
Beverley
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.
-
C.
Beverley
Beverley is a small rural town in Western Australia known for its agricultural community and historic country character.
-
D.
Beresford
Beresford is a surname most notably associated with Australian film director Bruce Beresford, known for works such as "Driving Miss Daisy."
-
E.
Bewdley
Bewdley is a historic riverside town in Worcestershire, England, known for its Georgian architecture and picturesque setting on the River Severn.
- 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_69d85cd3a3c881908c71fc424d459c17 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded7613cec8190ac25e3f68c5d0edf |
completed | April 15, 2026, 12:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe96aa3c888190a65e7b3c3b130131 |
completed | May 9, 2026, 2:06 a.m. |
Created at: April 10, 2026, 2:55 a.m.