Triple
T22508035
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Museum Insel Hombroich |
E556439
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Neuss-Holzheim |
—
|
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: Neuss-Holzheim | Statement: [Museum Insel Hombroich, locatedNear, Neuss-Holzheim]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Neuss-Holzheim Context triple: [Museum Insel Hombroich, locatedNear, Neuss-Holzheim]
-
A.
Neuß
chosen
Neuß is an alternative spelling of Neuss, a historic city on the Rhine in North Rhine-Westphalia, Germany.
-
B.
Eschweiler
Eschweiler is a town in western Germany near Aachen, known for its industrial history and location in the state of North Rhine-Westphalia.
-
C.
Würselen
Würselen is a town in western Germany’s state of North Rhine-Westphalia, located near the city of Aachen and known historically for its mining and industrial heritage.
-
D.
Raunheim
Raunheim is a town in the German state of Hesse, located near Frankfurt am Main and known for its proximity to major transportation routes and Frankfurt Airport.
-
E.
Burscheid
Burscheid is a small town in North Rhine-Westphalia, Germany, known for its location in the hilly Bergisches Land region and its mix of rural character and local industry.
- 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_69e11e555edc81909ca803587dafd747 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15d5dec7c8190bf71ef76a2dfe9a4 |
completed | April 29, 2026, 1:22 a.m. |
Created at: April 16, 2026, 8:50 p.m.