Triple

T16176609
Position Surface form Disambiguated ID Type / Status
Subject Arnold Gingrich E392579 entity
Predicate name P16 FINISHED
Object Arnold Gingrich E392579 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: Arnold Gingrich | Statement: [Arnold Gingrich, name, Arnold Gingrich]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Arnold Gingrich
Context triple: [Arnold Gingrich, name, Arnold Gingrich]
  • A. Arnold Gingrich chosen
    Arnold Gingrich was an American magazine editor best known as a co-founder and longtime editor of the influential men's magazine Esquire.
  • B. Willie Gingrich
    Willie Gingrich is a fast-talking, opportunistic lawyer character from Billy Wilder’s film "The Fortune Cookie," famously portrayed by Walter Matthau.
  • C. Gary Bauer
    Gary Bauer is an American conservative activist and former U.S. presidential candidate known for his strong evangelical Christian views and leadership roles in right-wing political organizations.
  • D. Frank Heinricht
    Frank Heinricht is a German business executive best known as the long-serving CEO of the specialty glass and materials technology company Schott AG.
  • E. Milton Moore
    Milton Moore was a cinematographer active during the silent film era, known for his work on early American cinema.
  • 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_69d87f1d32208190942e4e499a80c18c completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e21ebb7d048190beba4b584f87d5b0 completed April 17, 2026, 11:51 a.m.
NED1 Entity disambiguation (via context triple) batch_69fff7c11bc881909211a668f48092aa completed May 10, 2026, 3:13 a.m.
Created at: April 10, 2026, 5:02 a.m.