Triple
T18480760
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Berchtesgadener Hochthron |
E451548
|
entity |
| Predicate | accessibleFrom |
P1985
|
FINISHED |
| Object | Marktschellenberg |
—
|
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: Marktschellenberg | Statement: [Berchtesgadener Hochthron, accessibleFrom, Marktschellenberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marktschellenberg Context triple: [Berchtesgadener Hochthron, accessibleFrom, Marktschellenberg]
-
A.
Marktschellenberg
chosen
Marktschellenberg is a small Bavarian municipality in southeastern Germany, near the Austrian border and the Berchtesgaden Alps.
-
B.
Bleidenstadt
Bleidenstadt is a district of the town of Taunusstein in the Rheingau-Taunus region of Hesse, Germany, known for its historic church and small-town character.
-
C.
Beratzhausen
Beratzhausen is a market town in the Upper Palatinate region of Bavaria, Germany, known for its historic center and location in the scenic Laber valley.
-
D.
Schulenburg
Schulenburg is a district-level locality within the town of Pattensen in Lower Saxony, Germany.
-
E.
Scheibenberg
Scheibenberg is a small town in the Ore Mountains of Saxony, Germany, known for its historic mining heritage and distinctive basalt formations.
- 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_69d8d38465a0819099b9b42d2a662ac1 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e53066a7108190a50eda9b489c90ca |
completed | April 19, 2026, 7:43 p.m. |
Created at: April 10, 2026, 11:35 a.m.