Triple

T19305950
Position Surface form Disambiguated ID Type / Status
Subject Arlene Francis E482827 entity
Predicate radioShow P30454 FINISHED
Object Monitor 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: Monitor | Statement: [Arlene Francis, radioShow, Monitor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Monitor
Context triple: [Arlene Francis, radioShow, Monitor]
  • A. Monitor chosen
    Monitor was a long-running, innovative weekend radio program on NBC Radio that mixed news, music, interviews, and live remote segments into a continuous magazine-style broadcast.
  • B. Monitor
    The Monitor is a powerful cosmic being in DC Comics who oversees and attempts to protect the multiverse, most prominently during the "Crisis on Infinite Earths" storyline.
  • C. Monitor
    Monitor was the former independent regulator of NHS foundation trusts in England, overseeing their financial and governance performance before being merged into NHS Improvement.
  • D. Monitors
    Monitors are a powerful cosmic race in DC Comics that oversee and regulate the multiverse, particularly prominent in major crossover events like Final Crisis.
  • E. Computer
    Computer is a monthly peer-reviewed magazine published by the IEEE Computer Society that covers advances, trends, and research in computing and information technology.
  • 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_69d8e8d04d5c8190baa816986f2b1d1e completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e604c84fe08190869463bdd0324160 completed April 20, 2026, 10:49 a.m.
Created at: April 10, 2026, 1:31 p.m.