Triple
T22895309
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kreis Kamenz |
E568156
|
entity |
| Predicate | successor |
P78
|
FINISHED |
| Object | Landkreis 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: Landkreis Kamenz | Statement: [Kreis Kamenz, successor, Landkreis Kamenz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Landkreis Kamenz Context triple: [Kreis Kamenz, successor, Landkreis Kamenz]
-
A.
Ostalbkreis
Ostalbkreis is a rural district in the eastern part of Baden-Württemberg, Germany, known for its Swabian Alb landscapes and historic towns such as Aalen and Ellwangen.
-
B.
Kreis Kamenz
chosen
Kreis Kamenz was a former rural district in the German Democratic Republic, located in the Dresden administrative region of Saxony.
-
C.
Landkreis Spree-Neiße
Landkreis Spree-Neiße is a rural district in the state of Brandenburg in eastern Germany, bordering Poland and named after the Spree and Neisse rivers.
-
D.
Kreis Freital
Kreis Freital was a former administrative district in the Dresden region of Saxony, Germany, centered around the town of Freital.
-
E.
Landkreis Ostprignitz-Ruppin
Landkreis Ostprignitz-Ruppin is a rural district in the German state of Brandenburg, known for its lakes, forests, and historic towns such as Neuruppin.
- 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.