Triple
T15250646
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Meissen district |
E364508
|
entity |
| Predicate | containsMunicipality |
P852
|
FINISHED |
| Object | Radebeul |
E1132863
|
NE FINISHED |
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: Radebeul | Statement: [Meissen district, containsMunicipality, Radebeul]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Radebeul Context triple: [Meissen district, containsMunicipality, Radebeul]
-
A.
Radebeul
chosen
Radebeul is a town in the German state of Saxony, known for its wine-growing tradition and association with the writer Karl May.
-
B.
Radeberg
Radeberg is a small town in the German state of Saxony, known for its Radeberger Pilsner brewery and historic town center near Dresden.
-
C.
Weidenau
Weidenau is a district of the city of Siegen in North Rhine-Westphalia, Germany.
-
D.
Kühnitzsch
Kühnitzsch is a village-level subdivision of the town of Wurzen in the German state of Saxony.
-
E.
Riederau
Riederau is a small lakeside district of Dießen am Ammersee in Bavaria, Germany, known for its scenic location on the shores of Lake Ammersee.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d85a0dde7481908fc64d1e82d5d20d |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e007f62b9c8190b9ad40e2d1912b63 |
completed | April 15, 2026, 9:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffb593258081909dcaf2b37fd28e63 |
completed | May 9, 2026, 10:30 p.m. |
Created at: April 10, 2026, 3:13 a.m.