Triple
T17642866
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wüstegarten |
E429280
|
entity |
| Predicate | mountainRange |
P648
|
FINISHED |
| Object | Kellerwald |
—
|
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: Kellerwald | Statement: [Wüstegarten, mountainRange, Kellerwald]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kellerwald Context triple: [Wüstegarten, mountainRange, Kellerwald]
-
A.
Kellerwald
chosen
Kellerwald is a low mountain forest region in central Germany known for its ancient beech woodlands and protected national park status.
-
B.
Rheinwald
Rheinwald is a remote alpine valley region in southeastern Switzerland known for its dramatic mountain scenery and traditional villages.
-
C.
Schwanfeld
Schwanfeld is a small municipality in the Lower Franconia region of Bavaria, Germany, known for its rural character and historical roots.
-
D.
Radeberg
Radeberg is a small town in the German state of Saxony, known for its Radeberger Pilsner brewery and historic town center near Dresden.
-
E.
Ruppichteroth
Ruppichteroth is a small municipality in western Germany’s North Rhine-Westphalia region, characterized by its rural setting and proximity to the metropolitan area of Cologne-Bonn.
- 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_69d889e2c2608190b762e76d9b2262f1 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e46de7055c819080d315bb3637882b |
completed | April 19, 2026, 5:53 a.m. |
Created at: April 10, 2026, 6:03 a.m.