Triple

T11938721
Position Surface form Disambiguated ID Type / Status
Subject Hermann Kallenbach E284119 entity
Predicate name P16 FINISHED
Object Hermann Kallenbach E284119 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: Hermann Kallenbach | Statement: [Hermann Kallenbach, name, Hermann Kallenbach]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hermann Kallenbach
Context triple: [Hermann Kallenbach, name, Hermann Kallenbach]
  • A. Hermann Kallenbach chosen
    Hermann Kallenbach was a German-Jewish architect and close associate of Mahatma Gandhi who became one of his most devoted supporters during Gandhi’s years in South Africa.
  • B. Eberhard Diepgen
    Eberhard Diepgen is a German politician of the Christian Democratic Union who served for many years as mayor of Berlin, including during the city’s transition from division to reunification.
  • C. Otto Neuhoff
    Otto Neuhoff is a German local politician who has served as the mayor of the town of Bad Honnef.
  • D. Wilhelm Ohnesorge
    Wilhelm Ohnesorge was a German engineer and Nazi politician who served as the Reich Post Minister under Adolf Hitler and was involved in the regime’s communications and propaganda apparatus.
  • E. Otto Josten
    Otto Josten was the founder of Jostens, the American company best known for producing class rings, yearbooks, and other school-related memorabilia.
  • 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_69d6ab2ce9c48190b5d39511b524f666 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d903415d2481909d84e6727454b9fe completed April 10, 2026, 2:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69f70a114ccc81909bc428c40c01a461 completed May 3, 2026, 8:40 a.m.
Created at: April 8, 2026, 9:45 p.m.