Triple

T20140366
Position Surface form Disambiguated ID Type / Status
Subject My Little Pony: The Movie E491146 entity
Predicate producer P490 FINISHED
Object Brian Goldner 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: Brian Goldner | Statement: [My Little Pony: The Movie, producer, Brian Goldner]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Brian Goldner
Context triple: [My Little Pony: The Movie, producer, Brian Goldner]
  • A. Brian Goldner chosen
    Brian Goldner was an American business executive and longtime Hasbro CEO known for expanding the company’s brands into major film and television franchises.
  • B. George Goldner
    George Goldner was an influential American record executive and producer known for founding several prominent independent labels that helped shape early rock and roll, doo-wop, and Latin music.
  • C. Donald Goldsmith
    Donald Goldsmith is an American astronomer, science writer, and popularizer of cosmology known for making complex astrophysical concepts accessible to general audiences.
  • D. Marcus Goldman
    Marcus Goldman was a 19th-century German-born American investment banker best known as the founder of the global financial firm Goldman Sachs.
  • E. Bo Goldmann
    Bo Goldmann is a screenwriter best known for his work on the comedy film "Armed and Dangerous."
  • 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_69da6265f8f0819080b29c752a574088 completed April 11, 2026, 3:01 p.m.
NER Named-entity recognition batch_69e66798d59c81908ebcd6644b1b3744 completed April 20, 2026, 5:51 p.m.
Created at: April 11, 2026, 11:32 p.m.