Triple
T20748790
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zell am See District |
E510661
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Niedernsill |
—
|
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: Niedernsill | Statement: [Zell am See District, contains, Niedernsill]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Niedernsill Context triple: [Zell am See District, contains, Niedernsill]
-
A.
Niedernsill
chosen
Niedernsill is a small alpine municipality in the Zell am See district of Salzburg, Austria, known for its scenic mountain setting and outdoor recreation opportunities.
-
B.
Raaba-Grambach
Raaba-Grambach is a municipality in the Austrian state of Styria, located just southeast of the city of Graz.
-
C.
Biebelried
Biebelried is a small municipality in the Kitzingen district of Bavaria, Germany, known for its rural character and proximity to the Franconian wine region.
-
D.
Dürrnberg
Dürrnberg is a mountain area in the Austrian Alps known for its historic salt mines and scenic landscapes near the town of Hallein.
-
E.
Groß Dölln
Groß Dölln is a small village in Brandenburg, Germany, known for its surrounding forests, lakes, and the nearby former military airfield now used as a driving and testing center.
- 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_69e0b4c845e88190b4c5f3ae79291182 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c228af288190a20829d45c034c24 |
completed | April 21, 2026, 12:17 a.m. |
Created at: April 16, 2026, 12:34 p.m.