Triple

T8892710
Position Surface form Disambiguated ID Type / Status
Subject Linton Garner E211717 entity
Predicate familyName P18 FINISHED
Object Garner E5231 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: Garner | Statement: [Linton Garner, familyName, Garner]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Garner
Context triple: [Linton Garner, familyName, Garner]
  • A. Garner chosen
    Garner is a surname most notably associated with John Nance Garner, the 32nd vice president of the United States under Franklin D. Roosevelt.
  • B. Gilchrist
    Gilchrist is a surname of Scottish origin borne by various notable individuals in fields such as acting, sports, and public service.
  • C. Coker
    Coker is a residential and commercial neighborhood located within the Surulere area of Lagos, Nigeria.
  • D. Garner Ted Armstrong
    Garner Ted Armstrong was an American televangelist and religious broadcaster known for his influential role in the Worldwide Church of God and later for founding the Church of God International.
  • E. Eldridge
    Eldridge is an English-language surname of Old English origin, borne by various notable individuals across fields such as politics, the arts, and sports.
  • 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_69ca83907954819096d52a245b635841 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc61bb46c881909e579bb1926e5204 completed April 1, 2026, 12:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfabf795b08190bb4c45d6ede3b8b4 completed April 3, 2026, noon
Created at: March 30, 2026, 6:54 p.m.