Triple
T23306633
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kreis Sebnitz |
E590459
|
entity |
| Predicate | administrativeCenter |
P1474
|
FINISHED |
| Object | Sebnitz |
—
|
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: Sebnitz | Statement: [Kreis Sebnitz, administrativeCenter, Sebnitz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sebnitz Context triple: [Kreis Sebnitz, administrativeCenter, Sebnitz]
-
A.
Sebnitz
chosen
Sebnitz is a small town in eastern Germany known for its traditional artificial flower industry and its location in the scenic Saxon Switzerland region near the Czech border.
-
B.
Bannewitz
Bannewitz is a municipality in the Free State of Saxony in eastern Germany, located just south of the city of Dresden.
-
C.
Moritzburg
Moritzburg is a small Saxon town in eastern Germany, best known for its Baroque Moritzburg Castle and surrounding lakes and forests.
-
D.
Ribnitz-Damgarten
Ribnitz-Damgarten is a small town in northeastern Germany known as the “Bernsteinstadt” (Amber Town) for its long tradition of amber processing and its location near the Baltic Sea.
-
E.
Dennewitz
Dennewitz is a village in Brandenburg, Germany, historically notable as the site of a major 1813 battle during the Napoleonic Wars.
- 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_69e25d1c0ecc8190a355aa229f06d0e0 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1972846fc819092ca2b9590b2e177 |
completed | April 29, 2026, 5:29 a.m. |
Created at: April 17, 2026, 5:05 p.m.