Triple
T18948210
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ahr wine region |
E463570
|
entity |
| Predicate | hasSubregion |
P285
|
FINISHED |
| Object | Mayschoß |
—
|
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: Mayschoß | Statement: [Ahr wine region, hasSubregion, Mayschoß]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mayschoß Context triple: [Ahr wine region, hasSubregion, Mayschoß]
-
A.
Mayschoß
chosen
Mayschoß is a wine-growing village in western Germany’s Ahr valley, known for its steep vineyards and scenic river landscape.
-
B.
Bischofsmais
Bischofsmais is a small Bavarian municipality in southeastern Germany known for its forested landscape and outdoor recreation in the Bavarian Forest region.
-
C.
Bramsche
Bramsche is a town in Lower Saxony, Germany, known for its location near Osnabrück and its historical textile industry.
-
D.
Bodenmais
Bodenmais is a Bavarian spa and holiday resort town in the Bavarian Forest of Germany, known for its glassmaking tradition and outdoor recreation.
-
E.
Wimbachgries
Wimbachgries is a broad high-alpine gravel valley and hiking area in the Bavarian Alps, known for its impressive scree fields and dramatic mountain scenery.
- 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_69d8dcfec90481909e926be9767e5779 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d540e57c8190bb17fff6d4254320 |
completed | April 20, 2026, 7:26 a.m. |
Created at: April 10, 2026, 11:59 a.m.