Triple

T21980515
Position Surface form Disambiguated ID Type / Status
Subject Victoria Will E542824 entity
Predicate hasWorkedForPublication P94242 FINISHED
Object Variety 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: Variety | Statement: [Victoria Will, hasWorkedForPublication, Variety]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Variety
Context triple: [Victoria Will, hasWorkedForPublication, Variety]
  • A. Variety chosen
    Variety is a leading American entertainment trade magazine and website known for its coverage of film, television, theater, and the broader media industry.
  • B. Variété
    Variété is a multi-volume collection of essays by French writer Paul Valéry, blending literary criticism, philosophy, and reflections on art and culture.
  • C. Variety Speak
    "Variety Speak" is a comedic musical number from Animaniacs in which Yakko Warner humorously riffs on show-business jargon and entertainment-industry lingo.
  • D. Variety Girl
    Variety Girl is a 1947 Hollywood musical comedy film known for its star-studded Paramount studio cast and lighthearted, behind-the-scenes showbiz story.
  • E. At the Movies
    At the Movies was a long-running American film review television program, best known for featuring critics like Roger Ebert who popularized the "thumbs up/thumbs down" style of movie criticism.
  • 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_69e0c48136b081908831fa907cc02e18 completed April 16, 2026, 11:14 a.m.
NER Named-entity recognition batch_69f1248cf0388190b557d065beb662b5 completed April 28, 2026, 9:20 p.m.
Created at: April 16, 2026, 8:04 p.m.