Triple

T8605525
Position Surface form Disambiguated ID Type / Status
Subject Elle Netherlands E203786 entity
Predicate parentCompany P254 FINISHED
Object Hearst Magazines E37938 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: Hearst Magazines | Statement: [Elle Netherlands, parentCompany, Hearst Magazines]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hearst Magazines
Context triple: [Elle Netherlands, parentCompany, Hearst Magazines]
  • A. Hearst Magazines UK
    Hearst Magazines UK is a major British magazine publisher that produces a wide portfolio of lifestyle, fashion, and special-interest titles.
  • B. Condé Nast
    Condé Nast is a major global media company known for publishing influential magazines such as Vogue, The New Yorker, GQ, and Wired.
  • C. Time Inc.
    Time Inc. was a major American media company best known for publishing influential magazines such as Time, Life, Sports Illustrated, and Fortune.
  • D. Hearst Communications chosen
    Hearst Communications is a major American mass media and business information conglomerate with interests in television, cable networks, magazines, newspapers, and digital media.
  • E. Hearst
    Hearst is a small, predominantly Francophone town in northern Ontario, Canada, known for its forestry industry and strong French-Canadian cultural presence.
  • 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_69ca832c23e4819095a9f3eea4a21828 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cc46e9b6a881908f6a6c847519e5e5 completed March 31, 2026, 10:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69cef33f0aa0819091e101f822c53c0f completed April 2, 2026, 10:52 p.m.
Created at: March 30, 2026, 6:24 p.m.