Triple

T5160650
Position Surface form Disambiguated ID Type / Status
Subject Fast X E116426 entity
Predicate storyBy P1955 FINISHED
Object Dan Mazeau E502353 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: Dan Mazeau | Statement: [Fast X, storyBy, Dan Mazeau]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dan Mazeau
Context triple: [Fast X, storyBy, Dan Mazeau]
  • A. Dan Mazeau chosen
    Dan Mazeau is an American screenwriter known for working on major Hollywood action and fantasy films, including entries in the Fast & Furious franchise.
  • B. Dan Mazer
    Dan Mazer is a British screenwriter, director, and producer best known for his long-time collaboration with Sacha Baron Cohen on projects like Borat and Brüno.
  • C. Dan Janvey
    Dan Janvey is an American film producer known for his work on acclaimed independent films, including the Academy Award–winning "Nomadland."
  • D. Eric Lamonsoff
    Eric Lamonsoff is a bumbling yet big-hearted family man and close friend of Lenny Feder in the Grown Ups comedy film series.
  • E. Andrew Laeddis
    Andrew Laeddis is the true identity of U.S. Marshal Teddy Daniels, revealed as a delusional patient in the psychological thriller "Shutter Island."
  • 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_69bd445edb3881909b93b34d260717fc completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd79073a54819080cd1e8de6fe906a completed March 20, 2026, 4:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69beefa840288190ad0e1ab7af8b9c4c completed March 21, 2026, 7:21 p.m.
Created at: March 20, 2026, 1:44 p.m.