Triple
T21748594
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | District of Coburg |
E536850
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object | Untersiemau |
—
|
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: Untersiemau | Statement: [District of Coburg, hasMunicipality, Untersiemau]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Untersiemau Context triple: [District of Coburg, hasMunicipality, Untersiemau]
-
A.
Untersiemau
chosen
Untersiemau is a municipality in the Coburg district of northern Bavaria, Germany.
-
B.
Obergriesbach
Obergriesbach is a small municipality in the district of Aichach-Friedberg in the Bavarian region of Germany.
-
C.
Wittighausen
Wittighausen is a small municipality in the Main-Tauber district of Baden-Württemberg in southern Germany.
-
D.
Roßlau
Roßlau is a town in the German state of Saxony-Anhalt, now part of the city of Dessau-Roßlau, known historically as a regional railway and industrial hub.
-
E.
Weinböhla
Weinböhla is a small municipality in the German state of Saxony, known for its wine-growing tradition and location near the Elbe River between Dresden and Meißen.
- 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_69e0c46eab808190b848242d63a17c47 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f01a77e19c81909bf26f96aa41a7ce |
completed | April 28, 2026, 2:24 a.m. |
Created at: April 16, 2026, 6:50 p.m.