Triple
T10629762
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Möhnesee |
E250420
|
entity |
| Predicate | administrativeCenter |
P1474
|
FINISHED |
| Object | Körbecke |
E229756
|
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: Körbecke | Statement: [Möhnesee, administrativeCenter, Körbecke]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Körbecke Context triple: [Möhnesee, administrativeCenter, Körbecke]
-
A.
Körbecke
chosen
Körbecke is a village in North Rhine-Westphalia, Germany, situated on the shores of the Möhne Reservoir and known as a local recreational and holiday destination.
-
B.
Kleeberg
Kleeberg is a Polish surname most notably associated with General Franciszek Kleeberg, a commander in the early stages of World War II.
-
C.
Kienbach
Kienbach is a small river in Bavaria, Germany, that flows through the municipality of Herrsching am Ammersee into Lake Ammersee.
-
D.
Böbing
Böbing is a small municipality in the Weilheim-Schongau district of Bavaria, Germany, known for its rural setting in the Alpine foothills.
-
E.
Seckbach
Seckbach is a district in the east of Frankfurt am Main, Germany, known for its residential character and proximity to green spaces like the Lohrberg.
- 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_69d6aa5993448190a493b790b8f85010 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6df92f8388190a8bcff96809d8eb4 |
completed | April 8, 2026, 11:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d97a3e0e1481909c277be4c12b46ea |
completed | April 10, 2026, 10:31 p.m. |
Created at: April 8, 2026, 9 p.m.