Triple

T17128175
Position Surface form Disambiguated ID Type / Status
Subject Karl Lehmann E415651 entity
Predicate workLocation P7 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: [Karl Lehmann, workLocation, Freiburg im Breisgau]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Freiburg im Breisgau
Context triple: [Karl Lehmann, workLocation, 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_69d886d15af4819092f92f8a129763e6 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3f0285a408190ae5e4c4679c07fbf completed April 18, 2026, 8:57 p.m.
NED1 Entity disambiguation (via context triple) batch_6a014134601c81909f7f4a95d558e067 completed May 11, 2026, 2:38 a.m.
Created at: April 10, 2026, 5:36 a.m.