Triple
T18115806
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oberpfalz |
E433601
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Amberg-Sulzbach |
—
|
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: Amberg-Sulzbach | Statement: [Oberpfalz, contains, Amberg-Sulzbach]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Amberg-Sulzbach Context triple: [Oberpfalz, contains, Amberg-Sulzbach]
-
A.
Amberg-Sulzbach
chosen
Amberg-Sulzbach is a rural district in the Bavarian region of Upper Palatinate in Germany, known for its mix of historic towns, forests, and former mining areas.
-
B.
Amberg
Amberg is a historic town in Bavaria, Germany, known for its well-preserved medieval old town and former role as a regional administrative and trading center.
-
C.
Forchheim
Forchheim is a town in Upper Franconia, Bavaria, Germany, known for its historic old town and location along major regional rail and road routes.
-
D.
Nenzing
Nenzing is a small market town in the Austrian state of Vorarlberg, near the border with Liechtenstein and Switzerland.
-
E.
Holzkirchen
Holzkirchen is a market town in Upper Bavaria, Germany, known as a regional transport hub on the railway line between Munich and the Alpine foothills.
- 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_69d8b90916008190a1f110bd7ced5473 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4ddd58ea8819081e2bec5e591e093 |
completed | April 19, 2026, 1:51 p.m. |
Created at: April 10, 2026, 10:28 a.m.