Triple

T16032019
Position Surface form Disambiguated ID Type / Status
Subject Reggie E388868 entity
Predicate hasNotableBearerGivenName P110784 FINISHED
Object Reggie Nalder E830149 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: Reggie Nalder | Statement: [Reggie, hasNotableBearerGivenName, Reggie Nalder]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Reggie Nalder
Context triple: [Reggie, hasNotableBearerGivenName, Reggie Nalder]
  • A. Reggie Nalder chosen
    Reggie Nalder was an Austrian-born character actor best known for his gaunt, haunting features and chilling performances in horror and thriller films and television.
  • B. Reggie Perrin
    Reggie Perrin is a British television sitcom, adapted from the classic "The Fall and Rise of Reginald Perrin," about a middle-aged executive undergoing a comic midlife crisis.
  • C. Reggie McNamara
    Reggie McNamara was an early 20th-century Australian-born professional cyclist famed for his toughness and success in six-day racing events.
  • D. Darryl Hickman
    Darryl Hickman is an American former child actor and film and television performer known for roles in classic Hollywood films and later work as a television executive and acting coach.
  • E. Reggie Barlow
    Reggie Barlow is a former NFL wide receiver who became a successful American football coach at the professional and collegiate levels.
  • 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_69d86dada3808190825d5f80d72fbe88 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e21a00f6808190a60939ef7ce727a7 completed April 17, 2026, 11:31 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffcf35ae808190aeb154a273c32a70 completed May 10, 2026, 12:20 a.m.
Created at: April 10, 2026, 4:56 a.m.