Triple

T14117274
Position Surface form Disambiguated ID Type / Status
Subject Bernard Kroger E339804 entity
Predicate name P16 FINISHED
Object Bernard Kroger E339804 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: Bernard Kroger | Statement: [Bernard Kroger, name, Bernard Kroger]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bernard Kroger
Context triple: [Bernard Kroger, name, Bernard Kroger]
  • A. Bernard Kroger chosen
    Bernard Kroger was an American businessman and entrepreneur best known for founding the Kroger grocery store chain, which grew into one of the largest supermarket chains in the United States.
  • B. Larry "Pinto" Kroger
    Larry "Pinto" Kroger is a naive college freshman who becomes a central member of the misfit Delta Tau Chi fraternity in the comedy film *Animal House*.
  • C. David Sprecher
    David Sprecher is an author known for his work related to streets and urban environments.
  • D. Bernard Kohler
    Bernard Kohler is a person known primarily as a notable bearer of the surname Kohler, though specific widely recognized achievements or roles are not well documented.
  • E. Oskar Burger
    Oskar Burger is an evolutionary anthropologist known for his research on human life history, aging, and demographic patterns.
  • 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_69d81c6a95b481909e39111e0c1f31ee completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de609322ac8190bb389ca250882af5 completed April 14, 2026, 3:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcd0baa328819099511dfa7b9666d3 completed May 7, 2026, 5:49 p.m.
Created at: April 9, 2026, 10:22 p.m.