Triple

T11621958
Position Surface form Disambiguated ID Type / Status
Subject Bruce Beresford-Redman E275658 entity
Predicate employer P7 FINISHED
Object CBS E6070 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: CBS | Statement: [Bruce Beresford-Redman, employer, CBS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: CBS
Context triple: [Bruce Beresford-Redman, employer, CBS]
  • A. CBS
    CBS is a leading Danish university in Copenhagen specializing in business and economics education and research.
  • B. CBS
    CBS is the National Rail station code assigned to Coatbridge Sunnyside railway station in North Lanarkshire, Scotland.
  • C. CBS
    CBS is the commonly used abbreviation for the Commission for Basic Systems, a specialized body focused on foundational infrastructure and standards, likely within an international or governmental organizational context.
  • D. CBS chosen
    CBS is a major American broadcast television network known for airing a wide range of popular news, sports, and entertainment programming nationwide.
  • E. CBS
    CBS is a college within the University of California, Davis that focuses on education and research in the biological sciences.
  • 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_69d6aaf84b548190ac072e4fb89ae18f completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a122a3708190ab6513dad4c4fde7 completed April 10, 2026, 7:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69ee874fe11c81908b9d3a996bcc51d2 completed April 26, 2026, 9:44 p.m.
Created at: April 8, 2026, 9:39 p.m.