Triple
T21996266
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bezirk Cottbus |
E543213
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Senftenberg |
—
|
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: Senftenberg | Statement: [Bezirk Cottbus, contains, Senftenberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Senftenberg Context triple: [Bezirk Cottbus, contains, Senftenberg]
-
A.
Senftenberg
chosen
Senftenberg is a town in eastern Germany known for its lakeside recreation area and former lignite mining sites, located in the federal state of Brandenburg.
-
B.
Olbernhau
Olbernhau is a town in Germany’s Ore Mountains renowned for its traditional woodcraft industry, especially the production of Schwibbogen candle arches and other Christmas decorations.
-
C.
Meißen
Meißen is a historic town in the German state of Saxony, renowned for its porcelain manufacture and well-preserved medieval architecture along the Elbe River.
-
D.
Kretzschau
Kretzschau is a small municipality in the German state of Saxony-Anhalt that forms part of the wider Leipzig metropolitan area.
-
E.
Premnitz
Premnitz is a small town in the Havelland region of Brandenburg, Germany, situated on the Havel River and known historically for its chemical 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_69e11e2c814c8190837d072789000486 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f12765fb0c81908f7b7acda065ee2f |
completed | April 28, 2026, 9:32 p.m. |
Created at: April 16, 2026, 8:19 p.m.