Triple

T12468064
Position Surface form Disambiguated ID Type / Status
Subject SBS E297976 entity
Predicate hasYouTubePresence P57 FINISHED
Object SBS 뉴스 E297976 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: SBS 뉴스 | Statement: [SBS, hasYouTubePresence, SBS 뉴스]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: SBS 뉴스
Context triple: [SBS, hasYouTubePresence, SBS 뉴스]
  • A. KBS
    KBS is South Korea's national public broadcaster, known for its television, radio, and online services.
  • B. MBC
    MBC is a major South Korean television network known for broadcasting a wide range of entertainment, news, and cultural programs domestically and internationally.
  • C. SBS
    SBS is an elite British special forces unit of the Royal Navy specializing in maritime counter-terrorism, covert reconnaissance, and special operations.
  • D. SBS chosen
    SBS is a South Korean public broadcasting organization known for its nationwide television and radio networks and popular entertainment, news, and drama programming.
  • E. SBS
    SBS is the School of Biological Sciences at Nanyang Technological University, a major academic unit focused on education and research in the life 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_69d6ada270808190b1a2b2e7b02bb426 completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94db979c481908778188794b2c08e completed April 10, 2026, 7:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f63f2175c48190bbd28ad8c07434f0 completed May 2, 2026, 6:14 p.m.
Created at: April 8, 2026, 9:56 p.m.