Triple

T492733
Position Surface form Disambiguated ID Type / Status
Subject CNN E10223 entity
Predicate hasSisterChannel P6991 FINISHED
Object CNN International E10223 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: CNN International | Statement: [CNN, hasSisterChannel, CNN International]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: CNN International
Context triple: [CNN, hasSisterChannel, CNN International]
  • A. CNN chosen
    CNN is a major American cable news television channel known for pioneering 24-hour news coverage and live reporting from global events.
  • B. Sky News
    Sky News is a British 24-hour television news channel and digital news service known for live breaking news coverage in the UK and internationally.
  • C. Wikinews
    Wikinews is a free, collaboratively written online news source that is part of the Wikimedia family of projects.
  • D. BBC
    The BBC (British Broadcasting Corporation) is the United Kingdom’s publicly funded national broadcaster, known worldwide for producing and distributing television, radio, and online content.
  • E. Voice of America
    Voice of America is a U.S. government-funded international broadcaster that provides news and information in multiple languages to audiences around the world.
  • 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_69a2e847df8481909239ec08ccf1e376 completed Feb. 28, 2026, 1:06 p.m.
NER Named-entity recognition batch_69a2f0faab4881909f65f172198b5bd2 completed Feb. 28, 2026, 1:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69a47d2c33bc81909d0743ca3ef96c00 completed March 1, 2026, 5:53 p.m.
Created at: Feb. 28, 2026, 1:12 p.m.