Triple
T20748796
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zell am See District |
E510661
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Maishofen |
—
|
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: Maishofen | Statement: [Zell am See District, contains, Maishofen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maishofen Context triple: [Zell am See District, contains, Maishofen]
-
A.
Maishofen
chosen
Maishofen is a municipality in the Zell am See district of the Pinzgau region in the Austrian state of Salzburg, known for its alpine scenery and proximity to popular ski and lake destinations.
-
B.
Bodelshofen
Bodelshofen is a former locality in Baden-Württemberg, Germany, that was incorporated into the town of Wendlingen am Neckar.
-
C.
Altishofen
Altishofen is a municipality in the canton of Lucerne in central Switzerland, situated in the Wigger river valley.
-
D.
Waltershof
Waltershof is an industrial and port district of Hamburg, Germany, located within the borough of Hamburg-Mitte.
-
E.
Oschwand
Oschwand is a small locality in Switzerland known for its association with the Swiss painter Cuno Amiet, who lived and worked there.
- 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.