Triple
T14125740
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wupper basin |
E340025
|
entity |
| Predicate | containsTown |
P847
|
FINISHED |
| Object | Wülfrath |
E215193
|
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: Wülfrath | Statement: [Wupper basin, containsTown, Wülfrath]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wülfrath Context triple: [Wupper basin, containsTown, Wülfrath]
-
A.
Wülfrath
chosen
Wülfrath is a small town in North Rhine-Westphalia, western Germany, known historically for its limestone quarrying and rural character.
-
B.
Werne
Werne is a small town in North Rhine-Westphalia, Germany, known for its historic center and location along the Lippe River.
-
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.
Andernach
Andernach is a historic German town on the Rhine River in Rhineland-Palatinate, known for its medieval architecture and one of the world’s highest cold-water geysers.
-
E.
Rolfshagen
Rolfshagen is a locality in northern Germany historically notable as the place where Charles Frederick, Duke of Holstein-Gottorp, died.
- 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_69d81c6a95b481909e39111e0c1f31ee |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de6096976481909dc79066c5165a50 |
completed | April 14, 2026, 3:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd7a2fdd7c8190b2ebf5a18c8039f2 |
completed | May 8, 2026, 5:52 a.m. |
Created at: April 9, 2026, 10:22 p.m.