Triple
T18948208
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ahr wine region |
E463570
|
entity |
| Predicate | hasSubregion |
P285
|
FINISHED |
| Object | Ahrweiler |
—
|
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: Ahrweiler | Statement: [Ahr wine region, hasSubregion, Ahrweiler]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ahrweiler Context triple: [Ahr wine region, hasSubregion, Ahrweiler]
-
A.
Ahrweiler
chosen
Ahrweiler is a district in the German state of Rhineland-Palatinate, known for its wine-growing Ahr Valley and historic towns.
-
B.
Eschweiler
Eschweiler is a town in western Germany near Aachen, known for its industrial history and location in the state of North Rhine-Westphalia.
-
C.
Andernach
Andernach is a historic German town on the Rhine River in Rhineland-Palatinate, known for its medieval architecture and one of the world’s highest cold-water geysers.
-
D.
Wiehl
Wiehl is a river in North Rhine-Westphalia, Germany, that flows through the Bergisches Land region before joining the Agger.
-
E.
Wiehl
Wiehl is a small town in western Germany’s North Rhine-Westphalia region, known for its picturesque setting in the hilly Bergisches Land and its mix of rural charm and light industry.
- 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.