Triple

T19688455
Position Surface form Disambiguated ID Type / Status
Subject Kellogg E472772 entity
Predicate hasNotableBearer P458 FINISHED
Object George Kellogg (industrialist) 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: George Kellogg (industrialist) | Statement: [Kellogg, hasNotableBearer, George Kellogg (industrialist)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: George Kellogg (industrialist)
Context triple: [Kellogg, hasNotableBearer, George Kellogg (industrialist)]
  • A. George Kellogg (inventor) chosen
    George Kellogg was a 19th-century American inventor known for securing numerous patents across diverse fields, including machinery and industrial processes.
  • B. George Bradley Kellogg
    George Bradley Kellogg was a 19th-century American military officer who served as a Union Army general during the American Civil War.
  • C. John P. Kellogg
    John P. Kellogg is a notable individual associated with the Kellogg name, recognized for his contributions that distinguish him among bearers of the surname.
  • D. John Kellogg
    John Kellogg was an American character actor known for his supporting roles in mid-20th-century films and television.
  • E. Remington Kellogg
    Remington Kellogg was an American zoologist and paleontologist known for his pioneering research on marine mammals, particularly whales.
  • 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_69d8e515bef88190bc30781aea50537a completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e6420e5b788190a63ff6b83383b0e8 completed April 20, 2026, 3:11 p.m.
Created at: April 10, 2026, 1:45 p.m.