Triple
T12094752
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Heiligenhaus |
E288041
|
entity |
| Predicate | region |
P40
|
FINISHED |
| Object | Bergisches Land (edge) |
E300838
|
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: Bergisches Land (edge) | Statement: [Heiligenhaus, region, Bergisches Land (edge)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bergisches Land (edge) Context triple: [Heiligenhaus, region, Bergisches Land (edge)]
-
A.
Bergisches Land
chosen
Bergisches Land is a hilly, forested region in western Germany, east of the Rhine, known for its river valleys, reservoirs, and historic industrial towns.
-
B.
Bergkamen
Bergkamen is a town in North Rhine-Westphalia, Germany, known for its coal mining heritage and post-war planned urban development.
-
C.
Radevormwald
Radevormwald is a small historic town in North Rhine-Westphalia, western Germany, known for its hilly Bergisches Land landscape and traditional textile and metalworking industries.
-
D.
Wachtberg
Wachtberg is a municipality in the Rhein-Sieg district of North Rhine-Westphalia, Germany, known for its scenic location near Bonn and the Siebengebirge hills.
-
E.
Wülscheid
Wülscheid is a small locality within the Aegidienberg district of Bad Honnef in North Rhine-Westphalia, Germany.
- 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_69d6ab4964708190850585628b287b0c |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d91550ce508190babf5755e1553734 |
completed | April 10, 2026, 3:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f5f66edf7881908f29b5b40b9d020f |
completed | May 2, 2026, 1:04 p.m. |
Created at: April 8, 2026, 9:48 p.m.