Triple

T15931578
Position Surface form Disambiguated ID Type / Status
Subject Freiburg School E386335 entity
Predicate basedIn P40 FINISHED
Object Freiburg im Breisgau E179286 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: Freiburg im Breisgau | Statement: [Freiburg School, basedIn, Freiburg im Breisgau]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Freiburg im Breisgau
Context triple: [Freiburg School, basedIn, 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 (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_69d86da750008190987eb26be3f6c118 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e156a5b9348190962ddc1c35caf44f completed April 16, 2026, 9:37 p.m.
NED1 Entity disambiguation (via context triple) batch_6a000ec1091c8190a8e4c4db6180129a completed May 10, 2026, 4:51 a.m.
Created at: April 10, 2026, 4:52 a.m.