Triple
T22789197
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Winterberg |
E564061
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object | Oberhof |
—
|
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: Oberhof | Statement: [Winterberg, hasTwinTown, Oberhof]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oberhof Context triple: [Winterberg, hasTwinTown, Oberhof]
-
A.
Oberhof
chosen
Oberhof is a German winter sports town in Thuringia renowned for its biathlon, luge, and cross-country skiing facilities and World Cup events.
-
B.
Seiffen
Seiffen is a village in Germany’s Ore Mountains renowned for its traditional wooden toy-making and iconic Christmas decorations.
-
C.
Köppern
Köppern is a district of the town of Friedrichsdorf in the Hochtaunus region of Hesse, Germany.
-
D.
Stolpen
Stolpen is a small historic town in Saxony, Germany, best known for its medieval castle and its association with Countess Cosel.
-
E.
Riesa
Riesa is a town in the German state of Saxony, situated on the Elbe River and known historically as an important regional railway and industrial center.
- 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_69e2455500788190b4b33030461f3bbd |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17c33be7c8190ad22391a85fa000d |
completed | April 29, 2026, 3:34 a.m. |
Created at: April 17, 2026, 3:29 p.m.