Triple

T19888013
Position Surface form Disambiguated ID Type / Status
Subject Leon Breiner E477952 entity
Predicate name P16 FINISHED
Object Leon Breiner 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: Leon Breiner | Statement: [Leon Breiner, name, Leon Breiner]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Leon Breiner
Context triple: [Leon Breiner, name, Leon Breiner]
  • A. Leon Breiner chosen
    Leon Breiner was a white neighbor who was shot and killed during the 1925 Ossian Sweet incident in Detroit, a racially charged confrontation that led to a landmark civil rights trial.
  • B. Bruno Loerzer
    Bruno Loerzer was a prominent German First World War fighter ace who later became a high-ranking Luftwaffe general during the Nazi era.
  • C. René Mayer
    René Mayer was a French politician who served as Prime Minister of France and later became a leading figure in early European integration efforts.
  • D. Charles Bergstresser
    Charles Bergstresser was an American journalist and financier best known as one of the co-founders of The Wall Street Journal.
  • E. Abraham Palatnik
    Abraham Palatnik was a pioneering Brazilian artist and inventor best known for his groundbreaking kinetic and technological artworks that helped define the country's postwar avant-garde.
  • 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_69d8e51f32b08190b3687f4f60353250 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e6590c1b9c8190abbfaa04b80713b3 completed April 20, 2026, 4:49 p.m.
Created at: April 10, 2026, 1:52 p.m.