Triple

T18878665
Position Surface form Disambiguated ID Type / Status
Subject Michael Kinsley E461756 entity
Predicate employer P7 FINISHED
Object CNN 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: CNN | Statement: [Michael Kinsley, employer, CNN]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: CNN
Context triple: [Michael Kinsley, employer, CNN]
  • 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. NBC News Now
    NBC News Now is a free, ad-supported streaming news channel from NBC News that provides live, rolling coverage and original news programming across digital platforms.
  • C. NBC News
    NBC News is a major American television news division known for producing national and international news programs across broadcast and digital platforms.
  • D. CNN2
    CNN2 was the original name of HLN, a U.S. cable news channel that focused on headline news and brief, continuously updated reports.
  • E. NBC.com
    NBC.com is the official website and streaming platform of the NBC television network, offering full episodes, clips, and digital content from its shows.
  • 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_69d8dcfc3430819095ee6fc0eb4c06a5 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5c3cfc4408190a7ae91459f75be52 completed April 20, 2026, 6:12 a.m.
Created at: April 10, 2026, 11:57 a.m.