Triple

T19250635
Position Surface form Disambiguated ID Type / Status
Subject Rebecca Jarvis E481380 entity
Predicate previousEmployer P1910 FINISHED
Object CNBC 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: CNBC | Statement: [Rebecca Jarvis, previousEmployer, CNBC]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: CNBC
Context triple: [Rebecca Jarvis, previousEmployer, CNBC]
  • A. CNBC chosen
    CNBC is an American business news television channel known for its real-time financial market coverage and economic analysis.
  • B. Bloomberg Television
    Bloomberg Television is a global 24-hour business and financial news television network owned by Bloomberg L.P., known for its real-time market coverage and analysis.
  • C. Bloomberg News
    Bloomberg News is a global financial and business news organization known for its real-time market coverage, data-driven reporting, and multimedia journalism.
  • D. CBS MarketWatch
    CBS MarketWatch was an early online financial news and information service that evolved into the well-known business media brand now known simply as MarketWatch.
  • E. Bloomberg Radio
    Bloomberg Radio is a 24-hour business and financial news radio network operated by Bloomberg L.P., featuring market updates, economic analysis, and interviews with industry leaders.
  • 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_69d8e8cd9d1081908a181d02b88b59b8 completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e5fb3001308190913e24343769be8d completed April 20, 2026, 10:08 a.m.
Created at: April 10, 2026, 1:27 p.m.