Triple
T22994664
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kreis Bischofswerda |
E572153
|
entity |
| Predicate | administrativeCenter |
P1474
|
FINISHED |
| Object | Bischofswerda |
—
|
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: Bischofswerda | Statement: [Kreis Bischofswerda, administrativeCenter, Bischofswerda]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bischofswerda Context triple: [Kreis Bischofswerda, administrativeCenter, Bischofswerda]
-
A.
Bischofswerda
chosen
Bischofswerda is a small town in the Saxony region of eastern Germany, known as a local commercial and transport hub near the city of Dresden.
-
B.
Crimmitschau
Crimmitschau is a town in the German state of Saxony, historically known for its textile industry and located within the broader Leipzig metropolitan area.
-
C.
Riesa
Riesa is a town in the German state of Saxony, situated on the Elbe River and known historically as an important regional railway and industrial center.
-
D.
Liebenwalde
Liebenwalde is a small town and municipality in the Oberhavel district of the German state of Brandenburg.
-
E.
Zittau
Zittau is a historic town in the southeastern corner of Germany, known for its proximity to both the Czech and Polish borders and its well-preserved medieval 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_69e245b535808190adef8a9df3c584db |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f182f25af48190a98b7baeec824ae6 |
completed | April 29, 2026, 4:02 a.m. |
Created at: April 17, 2026, 3:50 p.m.