Triple
T22895307
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kreis Kamenz |
E568156
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object | Kamenz |
—
|
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: Kamenz | Statement: [Kreis Kamenz, namedAfter, Kamenz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kamenz Context triple: [Kreis Kamenz, namedAfter, Kamenz]
-
A.
Kamenz
chosen
Kamenz is a small town in eastern Germany best known as the birthplace of the Enlightenment writer and philosopher Gotthold Ephraim Lessing.
-
B.
Schleiz
Schleiz is a historic town in eastern Thuringia, Germany, known for its role as a former princely residence and for the nearby Schleizer Dreieck motor racing circuit.
-
C.
Bischofswerda
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.
-
D.
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.
-
E.
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.
- 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_69e2458c23ec81908fa2570692c6614f |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f17fc83d688190a8ab5ea0aad1e7ec |
completed | April 29, 2026, 3:49 a.m. |
Created at: April 17, 2026, 3:40 p.m.