Triple

T2980049
Position Surface form Disambiguated ID Type / Status
Subject Margaret Hoover E80486 entity
Predicate hasWorkedFor P11675 FINISHED
Object CNN 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 | Statement: [Margaret Hoover, hasWorkedFor, CNN]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: CNN
Context triple: [Margaret Hoover, hasWorkedFor, 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. CNN2
    CNN2 was the original name of HLN, a U.S. cable news channel that focused on headline news and brief, continuously updated reports.
  • D. ESPN News
    ESPN News is a 24-hour American sports news television channel providing continuous coverage, highlights, and analysis of major sporting events.
  • E. CBS News
    CBS News is a major American television and digital news division known for producing national and international news programs and journalism for the CBS network.
  • 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_69ad8b15f6ac8190be5fd16a33edcb4f completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad999e91788190a2d430dd0600a660 completed March 8, 2026, 3:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69b108f27d648190a7a58670fec8b74d completed March 11, 2026, 6:17 a.m.
Created at: March 8, 2026, 2:58 p.m.