Triple

T3690659
Position Surface form Disambiguated ID Type / Status
Subject Oberhavel E78334 entity
Predicate capital P234 FINISHED
Object Oranienburg E217564 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: Oranienburg | Statement: [Oberhavel, capital, Oranienburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oranienburg
Context triple: [Oberhavel, capital, Oranienburg]
  • A. Oranienburg chosen
    Oranienburg is a town in Brandenburg, Germany, historically known as the site of the Nazi Sachsenhausen concentration camp.
  • 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. Köthen
    Köthen is a town in the German state of Saxony-Anhalt, historically known as the residence of the Princes of Anhalt and as a significant center of Baroque music, including Johann Sebastian Bach’s tenure there.
  • D. Dessau
    Dessau is a German city best known for its association with the Bauhaus movement and its iconic modernist architecture.
  • E. Eilenburg
    Eilenburg is a small historic town in the German state of Saxony, situated on the Mulde River northeast of Leipzig.
  • 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_69ad85e285a081908f8cbfa9e2ed9b75 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc4e6147c8190ae358e8cc94f479c completed March 8, 2026, 6:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdf9f26be48190bf21b252a922ca69 completed March 21, 2026, 1:52 a.m.
Created at: March 8, 2026, 3:26 p.m.