Triple

T16001498
Position Surface form Disambiguated ID Type / Status
Subject Wolfgang Schmidt E388102 entity
Predicate region P40 FINISHED
Object Brandenburg, Germany E46660 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: Brandenburg, Germany | Statement: [Wolfgang Schmidt, region, Brandenburg, Germany]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Brandenburg, Germany
Context triple: [Wolfgang Schmidt, region, Brandenburg, Germany]
  • A. Berlin-Brandenburg, Germany
    Berlin-Brandenburg, Germany is a metropolitan region in northeastern Germany that includes the capital city of Berlin and the surrounding state of Brandenburg, serving as a major political, economic, and transportation hub.
  • B. Brandenburg an der Havel
    Brandenburg an der Havel is a historic town in eastern Germany, considered one of the cradles of the state of Brandenburg and known for its medieval architecture and waterways.
  • C. Brandenburg chosen
    Brandenburg is a federal state in northeastern Germany that surrounds Berlin and is known for its lakes, forests, and historic Prussian heritage.
  • D. Brandenburg
    Brandenburg is a small city in Meade County, Kentucky, situated along the Ohio River and serving as the county seat.
  • E. Döberitz, Germany
    Döberitz, Germany is a locality historically known for its military airfield and role in early German aviation testing and development.
  • 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_69d86daa562c81908aacc179c0fe8fb5 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e157fc6f308190b1ff8f81a976c494 completed April 16, 2026, 9:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffc3dba8e08190b6b26ac9a6854e50 completed May 9, 2026, 11:31 p.m.
Created at: April 10, 2026, 4:55 a.m.