Triple
T22349693
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kreis Nauen |
E552494
|
entity |
| Predicate | historicalCenter |
P2536
|
FINISHED |
| Object | town of Nauen |
—
|
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: town of Nauen | Statement: [Kreis Nauen, historicalCenter, town of Nauen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: town of Nauen Context triple: [Kreis Nauen, historicalCenter, town of Nauen]
-
A.
Nauen
chosen
Nauen is a historic town in the Havelland district of Brandenburg, Germany, known for its early radio transmission station and agricultural surroundings.
-
B.
Nauendorf
Nauendorf is a village in the German state of Saxony-Anhalt that forms part of the town of Wettin-Löbejün.
-
C.
Nassau (Lahn)
Nassau (Lahn) is a small historic town in western Germany, situated on the Lahn River and known for its medieval castle and scenic surroundings.
-
D.
Oeynhausen
Oeynhausen is a German family name most notably associated with the spa town of Bad Oeynhausen in North Rhine-Westphalia.
-
E.
Nennhausen
Nennhausen is a rural municipality in the Havelland district of Brandenburg, Germany, known for its historic manor house and surrounding natural landscapes.
- 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_69e11e4a0ad08190a385b4d343cf6524 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f1579ad6708190ba4af97a02d0758d |
completed | April 29, 2026, 12:58 a.m. |
Created at: April 16, 2026, 8:43 p.m.