Triple
T21995001
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dominikus Zimmermann |
E543181
|
entity |
| Predicate | workLocation |
P7
|
FINISHED |
| Object | Steingaden |
—
|
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: Steingaden | Statement: [Dominikus Zimmermann, workLocation, Steingaden]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Steingaden Context triple: [Dominikus Zimmermann, workLocation, Steingaden]
-
A.
Steingaden
chosen
Steingaden is a Bavarian municipality in southern Germany known for its picturesque alpine setting and proximity to the UNESCO-listed Wies Church.
-
B.
Rollingergrund
Rollingergrund is a district of Luxembourg City known for its residential character and proximity to central neighborhoods like Limpertsberg.
-
C.
Grafenried
Grafenried is a former Swiss municipality in the canton of Bern that has been incorporated into the larger municipality of Fraubrunnen.
-
D.
Hagsdorf
Hagsdorf is a small locality that forms part of the municipality of Persenbeug-Gottsdorf in Lower Austria.
-
E.
Geiersthal
Geiersthal is a small municipality in the Bavarian Forest region of southeastern Germany.
- 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_69e11e2c814c8190837d072789000486 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f127639bf48190800b3fa3c1527983 |
completed | April 28, 2026, 9:32 p.m. |
Created at: April 16, 2026, 8:19 p.m.