Triple

T16049357
Position Surface form Disambiguated ID Type / Status
Subject Merritt Butrick E389311 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: [Merritt Butrick, employer, CBS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: CBS
Context triple: [Merritt Butrick, 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
    CBS is the acronym for the Central Bank of Somalia, the country’s primary monetary authority responsible for issuing currency and overseeing financial stability.
  • E. CBS chosen
    CBS is a major American broadcast television network known for airing a wide range of popular news, sports, and entertainment programming nationwide.
  • 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_69d86dae698881908327ef2d67706cb9 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e18361083c8190abc84534265dc992 completed April 17, 2026, 12:48 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffe478bcc48190bdd4fcb7ec51caad completed May 10, 2026, 1:50 a.m.
Created at: April 10, 2026, 4:56 a.m.