Triple
T17583739
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hohle Fels |
E428266
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Schelklingen |
—
|
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: Schelklingen | Statement: [Hohle Fels, locatedNear, Schelklingen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Schelklingen Context triple: [Hohle Fels, locatedNear, Schelklingen]
-
A.
Schelklingen
chosen
Schelklingen is a small historic town in the Alb-Donau district of Baden-Württemberg in southern Germany, known for its picturesque setting near the Swabian Jura.
-
B.
Boblingen
Böblingen is a town in the German state of Baden-Württemberg, known for its automotive industry presence and proximity to Stuttgart.
-
C.
Crailsheim
Crailsheim is a town in the German state of Baden-Württemberg, known for its historical center and post-war reconstruction after heavy World War II damage.
-
D.
Schwerte
Schwerte is a town in North Rhine-Westphalia, Germany, known as a small industrial and commuter community near Dortmund.
-
E.
Meerbusch
Meerbusch is a town in the German state of North Rhine-Westphalia, situated on the west bank of the Rhine near Düsseldorf and known for its affluent residential areas and green surroundings.
- 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_69d889e1030481909950e140c63255b9 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e463d015fc8190b2dd897026d6fcb5 |
completed | April 19, 2026, 5:10 a.m. |
Created at: April 10, 2026, 5:50 a.m.