Triple

T19565606
Position Surface form Disambiguated ID Type / Status
Subject Archbishop of Freiburg E489573 entity
Predicate seat P75 FINISHED
Object Freiburg im Breisgau 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: Freiburg im Breisgau | Statement: [Archbishop of Freiburg, seat, Freiburg im Breisgau]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Freiburg im Breisgau
Context triple: [Archbishop of Freiburg, seat, Freiburg im Breisgau]
  • A. Freiburg im Breisgau chosen
    Freiburg im Breisgau is a historic university city in southwest Germany known for its medieval old town, eco-friendly urban planning, and location at the edge of the Black Forest.
  • B. Freiburg
    Freiburg is the German name for the bilingual Swiss city and canton capital of Fribourg, located in western Switzerland.
  • C. Karlsruhe
    Karlsruhe is a major city in southwestern Germany best known as the seat of the country’s highest courts and a central hub of German constitutional jurisprudence.
  • D. Pforzheim
    Pforzheim is a city in southwestern Germany, historically known for its jewelry and watchmaking industry and its heavy destruction during World War II.
  • E. Böblingen
    Böblingen is a town in the German state of Baden-Württemberg, near Stuttgart, known for its automotive and technology industries and its role as a regional economic center.
  • 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_69d8e8dc5d8c8190a6d7bd8864f43ca0 completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e63f777cf081909312b46ac09bce7c completed April 20, 2026, 3 p.m.
Created at: April 10, 2026, 1:42 p.m.