Triple
T21605926
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kreis Belzig |
E533171
|
entity |
| Predicate | administrativeCenter |
P1474
|
FINISHED |
| Object | Belzig |
—
|
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: Belzig | Statement: [Kreis Belzig, administrativeCenter, Belzig]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Belzig Context triple: [Kreis Belzig, administrativeCenter, Belzig]
-
A.
Belzig
chosen
Belzig is a small historic town in the German state of Brandenburg, known for its medieval castle and spa facilities.
-
B.
Lippendorf
Lippendorf is a village in Saxony, Germany, historically notable as the birthplace of Katharina von Bora, the wife of Martin Luther.
-
C.
Seelow
Seelow is a small town in eastern Brandenburg, Germany, best known today as the administrative center of the Märkisch-Oderland district and for its proximity to the historic Seelow Heights battlefield of World War II.
-
D.
Zossen
Zossen is a town in Brandenburg, Germany, historically notable as a major military command center, including serving as a key headquarters area during the Soviet occupation after World War II.
-
E.
Trebbin
Trebbin is a small town in the German state of Brandenburg, located southwest of Berlin.
- 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_69e0c46364608190a337dc8720dc2a35 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef17e5783481909db36c388f3ae227 |
completed | April 27, 2026, 8:01 a.m. |
Created at: April 16, 2026, 6:33 p.m.