Triple

T10059057
Position Surface form Disambiguated ID Type / Status
Subject George William, Elector of Brandenburg E208935 entity
Predicate birthPlace P1 FINISHED
Object Cölln E83946 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: Cölln | Statement: [George William, Elector of Brandenburg, birthPlace, Cölln]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cölln
Context triple: [George William, Elector of Brandenburg, birthPlace, Cölln]
  • A. Cölln chosen
    Cölln was a historic town on the River Spree that, together with Berlin, formed the core of what later became the city of Berlin.
  • B. Falkensee
    Falkensee is a town in the Havelland district of Brandenburg, Germany, situated just west of Berlin and functioning largely as a residential suburb of the capital.
  • C. Grevesmühlen
    Grevesmühlen is a small town in the German state of Mecklenburg-Vorpommern, known as a local administrative and service center in the north of the country.
  • D. Brühl
    Brühl is a German town in North Rhine-Westphalia known for its historic architecture and as the birthplace of surrealist artist Max Ernst.
  • E. Luisenstadt
    Luisenstadt is a historic former district of Berlin, Germany, known for its 19th-century urban development and significant cultural and architectural heritage.
  • 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_69ca836094408190a36a1ea7e9a86fcd completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cdcfb0f17c8190a8c0cfb02863537d completed April 2, 2026, 2:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69d29a6779348190ab8db058fb6e5ce1 completed April 5, 2026, 5:22 p.m.
Created at: March 30, 2026, 8:57 p.m.