Triple

T19832959
Position Surface form Disambiguated ID Type / Status
Subject The Joel McHale Show with Joel McHale E476507 entity
Predicate executiveProducer P7225 FINISHED
Object Mike Farah 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: Mike Farah | Statement: [The Joel McHale Show with Joel McHale, executiveProducer, Mike Farah]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mike Farah
Context triple: [The Joel McHale Show with Joel McHale, executiveProducer, Mike Farah]
  • A. Mike Farah chosen
    Mike Farah is an American television and film producer best known as the longtime executive producer and CEO of Funny or Die.
  • B. Sean Faris
    Sean Faris is an American actor and model best known for his roles in films like "Never Back Down" and television series such as "Life As We Know It."
  • C. Brian Farnon
    Brian Farnon was a Canadian-born musician, arranger, and conductor known for his work in light orchestral music and as the father of actress Charmian Carr.
  • D. Lewis Farrell
    Lewis Farrell is the charming, commitment-averse florist who becomes the romantic lead in the film "Bed of Roses."
  • E. Johnny Farrell
    Johnny Farrell is a small-time gambler who becomes entangled in a dangerous love triangle and criminal intrigue in the classic 1946 film noir "Gilda."
  • 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_69d8e51c7c188190b926f3a2a7b5f881 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e656cf7e488190b4be28b5e7b363bf completed April 20, 2026, 4:39 p.m.
Created at: April 10, 2026, 1:50 p.m.