Triple
T15955804
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Salzlandkreis |
E386930
|
entity |
| Predicate | capital |
P234
|
FINISHED |
| Object | Bernburg (Saale) |
E506183
|
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: Bernburg (Saale) | Statement: [Salzlandkreis, capital, Bernburg (Saale)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bernburg (Saale) Context triple: [Salzlandkreis, capital, Bernburg (Saale)]
-
A.
Bernburg
chosen
Bernburg is a town in the German state of Saxony-Anhalt, historically known for its castle overlooking the Saale River and its role as an industrial and cultural center in the region.
-
B.
Berga an der Elster
Berga an der Elster is a small town in Thuringia, Germany, historically known for hosting a Nazi concentration camp subcamp during World War II.
-
C.
Naumburg (Saale)
Naumburg (Saale) is a historic town in the German state of Saxony-Anhalt, renowned for its medieval cathedral and well-preserved old town.
-
D.
Treuenbrietzen
Treuenbrietzen is a historic town in the German state of Brandenburg, known for its medieval architecture and role in Reformation-era history.
-
E.
Bernsdorf
Bernsdorf is a locality within the town of Flöha in the Free State of Saxony, Germany.
- 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_69d86da882448190a82ea962fe343b79 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e156fb29848190a55cabb49cb19575 |
completed | April 16, 2026, 9:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffbe7c8ef081908fa6da7975c271f6 |
completed | May 9, 2026, 11:08 p.m. |
Created at: April 10, 2026, 4:53 a.m.