Triple

T713045
Position Surface form Disambiguated ID Type / Status
Subject Arrested Development E14250 entity
Predicate executiveProducer P7225 FINISHED
Object Mitchell Hurwitz E99817 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: Mitchell Hurwitz | Statement: [Arrested Development, executiveProducer, Mitchell Hurwitz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mitchell Hurwitz
Context triple: [Arrested Development, executiveProducer, Mitchell Hurwitz]
  • A. Mitchell Hurwitz chosen
    Mitchell Hurwitz is an American television writer and producer best known for creating the critically acclaimed sitcom "Arrested Development."
  • B. Paul Vogel
    Paul Vogel was an American cinematographer best known for his work on classic Hollywood films, including the Oscar-winning "Battleground."
  • C. Seth Gordon
    Seth Gordon is an American film and television director known for his work on comedies such as "Horrible Bosses" and the documentary "The King of Kong: A Fistful of Quarters."
  • D. Dan Scanlon
    Dan Scanlon is an American filmmaker and animator best known for his work as a director and writer at Pixar Animation Studios.
  • E. Craig Zadan
    Craig Zadan was an American film, television, and theater producer best known for his work on musical adaptations and live TV musicals, including projects like "Chicago" and NBC's live musical 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_69a4934a36e081909e7abef98b898a4e completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a55ee4fc81909358659ec3bc435f completed March 1, 2026, 8:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7a3a8bcc8819091c785ad953ddc54 completed March 4, 2026, 3:14 a.m.
Created at: March 1, 2026, 7:36 p.m.