Triple

T6498907
Position Surface form Disambiguated ID Type / Status
Subject Lawrence Harvey Zeiger E148828 entity
Predicate employer P7 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: [Lawrence Harvey Zeiger, employer, CNN]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: CNN
Context triple: [Lawrence Harvey Zeiger, 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. ESPN News
    ESPN News is a 24-hour American sports news television channel providing continuous coverage, highlights, and analysis of major sporting events.
  • 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_69c687e9ad288190bae5bcac9c8ac855 completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c68ad00d10819096c43f311388fa3a completed March 27, 2026, 1:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6cb16d6a48190b6871e55fda2e1a6 completed March 27, 2026, 6:23 p.m.
Created at: March 27, 2026, 1:41 p.m.