Triple

T2756722
Position Surface form Disambiguated ID Type / Status
Subject John Nance Garner E61118 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: [John Nance Garner, familyName, Garner]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Garner
Context triple: [John Nance 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. 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.
  • C. 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.
  • D. Vance
    Vance is a surname most prominently associated with Emmy and Tony Award–winning American actor Courtney B. Vance.
  • E. Tucker
    Tucker is a surname most notably associated with Albert W. Tucker, a Canadian-American mathematician and game theorist known for his contributions to topology and the formalization of the prisoner's dilemma.
  • 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_69ab4b7a85bc819094a349b84beb1f2c completed March 6, 2026, 9:47 p.m.
NER Named-entity recognition batch_69abdb8a292c8190ab3982434805241a completed March 7, 2026, 8:02 a.m.
NED1 Entity disambiguation (via context triple) batch_69afbbdf650c8190baa020143b51f94b completed March 10, 2026, 6:36 a.m.
Created at: March 6, 2026, 9:56 p.m.