Triple

T179778
Position Surface form Disambiguated ID Type / Status
Subject Sylvia Nasar E3657 entity
Predicate employer P7 FINISHED
Object Fortune magazine E20322 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: Fortune magazine | Statement: [Sylvia Nasar, employer, Fortune magazine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fortune magazine
Context triple: [Sylvia Nasar, employer, Fortune magazine]
  • A. Fortune magazine chosen
    Fortune magazine is a prominent American business publication known for its in-depth reporting on corporate affairs, economics, and its influential rankings such as the Fortune 500.
  • B. Time magazine
    Time magazine is a long-running American weekly news magazine known for its influential coverage of global events, politics, and culture.
  • 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. Life magazine
    Life magazine was a hugely influential American weekly publication best known for its pioneering photojournalism and vivid visual coverage of 20th-century events and culture.
  • E. Newsweek magazine
    Newsweek magazine is a long-running American weekly news publication known for its national and international news coverage, analysis, and commentary.
  • 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_69a25374990081909766d30c79a18e0e completed Feb. 28, 2026, 2:31 a.m.
NER Named-entity recognition batch_69a25901a9188190b8f510bec8c8e7f2 completed Feb. 28, 2026, 2:54 a.m.
NED1 Entity disambiguation (via context triple) batch_69a2f0b71080819086362f6036b41162 completed Feb. 28, 2026, 1:42 p.m.
Created at: Feb. 28, 2026, 2:39 a.m.