Triple

T18069300
Position Surface form Disambiguated ID Type / Status
Subject Peter Elkind E432379 entity
Predicate employer P7 FINISHED
Object Fortune magazine 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: Fortune magazine | Statement: [Peter Elkind, employer, Fortune magazine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fortune magazine
Context triple: [Peter Elkind, 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. Forbes
    Forbes is a global media company best known for its business magazine that ranks and profiles the world’s wealthiest individuals, companies, and influential leaders.
  • C. Forbes
    Forbes is a historic rural town in central-west New South Wales, Australia, known for its agricultural industry and heritage architecture along the Lachlan River.
  • D. Inc. magazine
    Inc. magazine is a U.S. business publication best known for its coverage of entrepreneurship, fast-growing private companies, and startup culture, including its annual Inc. 5000 rankings.
  • E. Money magazine
    Money magazine is a personal finance publication known for its rankings and advice on investing, saving, and quality-of-life evaluations of cities and communities.
  • 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_69d8b9070cac81909fa9473fb1c3f1c7 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4ccebff748190b41d2edd93994c67 completed April 19, 2026, 12:39 p.m.
Created at: April 10, 2026, 10:26 a.m.