Triple

T16209387
Position Surface form Disambiguated ID Type / Status
Subject King of the Hill E393416 entity
Predicate executiveProducer P7225 FINISHED
Object Michael Rotenberg 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: Michael Rotenberg | Statement: [King of the Hill, executiveProducer, Michael Rotenberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Michael Rotenberg
Context triple: [King of the Hill, executiveProducer, Michael Rotenberg]
  • A. Michael Rotenberg chosen
    Michael Rotenberg is a television producer and manager best known for his work on popular comedy series including It's Always Sunny in Philadelphia.
  • B. Michael Nudelman
    Michael Nudelman was an Israeli politician and Knesset member known for representing Russian-speaking immigrants and serving in several immigrant-focused political parties.
  • C. Michael Rachmil
    Michael Rachmil is a film producer best known for his work on the 1987 romantic comedy "Roxanne" starring Steve Martin.
  • D. Michael Braverman
    Michael Braverman is a television producer best known for his work as an executive producer on reality and documentary-style TV series.
  • E. Michael D. Rosenthal
    Michael D. Rosenthal is a writer best known as the author whose work inspired the "Twilight Zone" episode "A Kind of Stopwatch."
  • 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_69d87f1f5bd08190bd01cac0d5b9d2ef completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e22711e4fc8190bf7a9f0c59b7889f completed April 17, 2026, 12:26 p.m.
Created at: April 10, 2026, 5:03 a.m.