Triple
T17847332
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Karol Scheibler |
E445698
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object | Monschau |
—
|
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: Monschau | Statement: [Karol Scheibler, placeOfBirth, Monschau]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Monschau Context triple: [Karol Scheibler, placeOfBirth, Monschau]
-
A.
Monschau
chosen
Monschau is a historic small town in western Germany’s Eifel region, known for its well-preserved half-timbered houses, medieval center, and scenic setting along the Rur River.
-
B.
Kettwig
Kettwig is a historic district of the German city of Essen, known for its picturesque old town along the Ruhr River and scenic lakeside surroundings.
-
C.
Kreuztal
Kreuztal is a town in the Siegen-Wittgenstein district of North Rhine-Westphalia, Germany, known as an industrial and transport hub in the Siegerland region.
-
D.
Neuß
Neuß is an alternative spelling of Neuss, a historic city on the Rhine in North Rhine-Westphalia, Germany.
-
E.
Wermelskirchen
Wermelskirchen is a small town in North Rhine-Westphalia, Germany, known for its location in the hilly Bergisches Land region and its traditional half-timbered architecture.
- 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_69d8b9f26f18819089c9e43250bee6ae |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e48ffb35248190a80a428686e06d87 |
completed | April 19, 2026, 8:19 a.m. |
Created at: April 10, 2026, 10:16 a.m.