Triple
T12045494
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | City History Museum Dessau |
E286775
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Dessau-Roßlau |
E102721
|
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: Dessau-Roßlau | Statement: [City History Museum Dessau, locatedIn, Dessau-Roßlau]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dessau-Roßlau Context triple: [City History Museum Dessau, locatedIn, Dessau-Roßlau]
-
A.
Dessau
chosen
Dessau is a German city best known for its association with the Bauhaus movement and its iconic modernist architecture.
-
B.
Sangerhausen
Sangerhausen is a town in the German state of Saxony-Anhalt, known for its historic mining heritage and its renowned Europa-Rosarium rose garden.
-
C.
Zerbst
Zerbst is a historic town in Saxony-Anhalt, Germany, known as the birthplace of Catherine the Great and for its former role as a princely residence.
-
D.
Oranienburg
Oranienburg is a town in Brandenburg, Germany, historically known as the site of the Nazi Sachsenhausen concentration camp.
-
E.
Mahlsdorf
Mahlsdorf is a locality in the borough of Marzahn-Hellersdorf in eastern Berlin, Germany, known for its residential character and historic village center.
- 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_69d6ab4780948190bdb9f7620c2ac27e |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9041fe3b0819094b82a6b17ac59c3 |
completed | April 10, 2026, 2:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6c0d2818c8190a1bea5f1fc8a9f59 |
completed | May 3, 2026, 3:28 a.m. |
Created at: April 8, 2026, 9:47 p.m.