Triple

T9406800
Position Surface form Disambiguated ID Type / Status
Subject Dorothy Parker E226606 entity
Predicate employer P7 FINISHED
Object Vogue E39386 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: Vogue | Statement: [Dorothy Parker, employer, Vogue]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vogue
Context triple: [Dorothy Parker, employer, Vogue]
  • A. Vogue chosen
    Vogue is a leading international fashion and lifestyle magazine renowned for its influential coverage of style, beauty, culture, and high-profile personalities.
  • B. Vogue
    "Vogue" is a 1990 dance-pop song by Madonna, renowned for popularizing voguing and becoming one of her most iconic and influential hits.
  • C. The Vogue
    The Vogue was a pivotal Seattle nightclub that became a key hub for the emerging grunge scene in the late 1980s and early 1990s.
  • D. Vogue Italia
    Vogue Italia is the Italian edition of the international fashion magazine Vogue, renowned for its avant-garde photography, artistic editorial direction, and influential role in high fashion.
  • E. Vogue Brazil
    Vogue Brazil is the Brazilian edition of the international fashion and lifestyle magazine Vogue, featuring content tailored to Brazil’s fashion industry, culture, and trends.
  • 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_69ca843280488190bc65600e843ef9e6 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd51c3fc988190ac34cc9e09f8ebfc completed April 1, 2026, 5:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69d12228d8148190814646881e1f2d98 completed April 4, 2026, 2:37 p.m.
Created at: March 30, 2026, 7:47 p.m.