Triple
T3737592
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trauen |
E79621
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Faßberg |
E334711
|
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: Faßberg | Statement: [Trauen, locatedNear, Faßberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Faßberg Context triple: [Trauen, locatedNear, Faßberg]
-
A.
Ennigerloh
Ennigerloh is a small town in the German state of North Rhine-Westphalia, known as the birthplace of mathematician Karl Weierstrass.
-
B.
Ronsdorf
Ronsdorf is a district of the German city of Wuppertal in North Rhine-Westphalia, historically known as an independent town in the Bergisches Land region.
-
C.
Werdau
Werdau is a town in the Free State of Saxony in eastern Germany, historically known for its textile and engineering industries.
-
D.
Barsinghausen
chosen
Barsinghausen is a town in Lower Saxony, Germany, located near Hanover and known historically for its mining industry and proximity to the Deister hills.
-
E.
Suhl
Suhl is a city in central Germany known historically as a center of firearms manufacturing and located in the federal state of Thuringia.
- 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_69ad8b115610819095b02007da5ca3cb |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcb3e9248819098d481fe29e1c628 |
completed | March 8, 2026, 7:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5f59074e881908d346937da0b056e |
completed | March 14, 2026, 11:56 p.m. |
Created at: March 8, 2026, 3:34 p.m.