Triple

T21040371
Position Surface form Disambiguated ID Type / Status
Subject Reg Varney E518304 entity
Predicate familyName P18 FINISHED
Object Varney 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: Varney | Statement: [Reg Varney, familyName, Varney]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Varney
Context triple: [Reg Varney, familyName, Varney]
  • A. Varney chosen
    Varney is the surname of American actor and comedian Jim Varney, best known for portraying the character Ernest P. Worrell in films and television.
  • B. Moneague
    Moneague is a rural village in Jamaica known for its karst landscape, seasonal lake, and location along the main road through Saint Ann Parish.
  • C. Walter Varney
    Walter Varney was an early American aviation pioneer and entrepreneur who founded airlines that later evolved into major U.S. carriers such as United Airlines and Continental Airlines.
  • D. Val Valentine
    Val Valentine was a screenwriter known for his work on early 20th-century Hollywood films, including the musical comedy "Going Hollywood."
  • E. Mr. Vandemar
    Mr. Vandemar is a brutal, seemingly immortal assassin and one of the primary antagonists in Neil Gaiman’s urban fantasy novel "Neverwhere."
  • 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_69e0b50438e08190917e2538bb8bc034 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e6fceed9148190903adb3b55f65242 completed April 21, 2026, 4:28 a.m.
Created at: April 16, 2026, 2:15 p.m.