Triple
T19494143
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daubeny |
E487725
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Daubeney |
—
|
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: Daubeney | Statement: [Daubeny, hasVariant, Daubeney]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Daubeney Context triple: [Daubeny, hasVariant, Daubeney]
-
A.
Daubeny
chosen
Daubeny is an English surname derived from the Norman French family name d’Aubigny.
-
B.
Keadby
Keadby is a village in North Lincolnshire, England, known for its location on the River Trent and its nearby power station and transport links.
-
C.
Baumberge
Baumberge is a low mountain and hill range in the Münsterland region of North Rhine-Westphalia, Germany, known for its forests, hiking trails, and scenic landscapes.
-
D.
Dunkley
Dunkley is an English-origin surname borne by various notable individuals, including politicians, athletes, and public figures.
-
E.
Tealby
Tealby is a picturesque rural village in eastern England, known for its traditional stone cottages and scenic setting within the Lincolnshire countryside.
- 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_69d8e8d9d1c88190b01cd78b8be49384 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6349002788190afe7831d008d440f |
completed | April 20, 2026, 2:13 p.m. |
Created at: April 10, 2026, 1:40 p.m.