Triple
T22383628
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Siebengebirge |
E553337
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Nonnenstromberg |
—
|
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: Nonnenstromberg | Statement: [Siebengebirge, contains, Nonnenstromberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nonnenstromberg Context triple: [Siebengebirge, contains, Nonnenstromberg]
-
A.
Nonnenstromberg
chosen
Nonnenstromberg is a wooded hill in the Siebengebirge range near the Rhine in Germany, known for its natural scenery and hiking trails.
-
B.
Witzmannsberg
Witzmannsberg is a small rural municipality in the Bavarian region of Lower Bavaria, Germany, known for its scenic countryside and traditional village character.
-
C.
Festungsberg
Festungsberg is a prominent hill in Salzburg, Austria, best known as the site of the medieval Hohensalzburg Fortress overlooking the city.
-
D.
Wackersberg
Wackersberg is a rural Bavarian municipality in southern Germany, known for its scenic Alpine foothills and traditional village character.
-
E.
Oberhalbstein
Oberhalbstein is a high Alpine valley and region in the canton of Graubünden, Switzerland, known for its Romansh-speaking communities and mountain landscapes.
- 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_69e11e4cf87c8190a1ff474daec326b7 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f1582d8e548190a7330de49d519675 |
completed | April 29, 2026, 1 a.m. |
Created at: April 16, 2026, 8:45 p.m.