Triple

T20117549
Position Surface form Disambiguated ID Type / Status
Subject It's a Mad, Mad, Mad, Mad World E490506 entity
Predicate screenwriter P2831 FINISHED
Object William Rose 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: William Rose | Statement: [It's a Mad, Mad, Mad, Mad World, screenwriter, William Rose]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: William Rose
Context triple: [It's a Mad, Mad, Mad, Mad World, screenwriter, William Rose]
  • A. William Rose chosen
    William Rose was an American screenwriter best known for his work on classic comedies such as "The Russians Are Coming, the Russians Are Coming" and "Guess Who's Coming to Dinner."
  • B. Charles Gillibert
    Charles Gillibert is a French film producer known for backing acclaimed auteur-driven films such as "Clouds of Sils Maria," "Personal Shopper," and "Mustang."
  • C. Thomas Mayne
    Thomas Mayne was an Australian food scientist best known for creating the chocolate malted milk drink Milo in the 1930s.
  • D. William Irwin
    William Irwin was a 19th-century American politician who served as Governor of California from 1875 to 1880.
  • E. William March
    William March was an American author best known for his 1954 psychological horror novel "The Bad Seed," which became a classic of the genre and inspired multiple adaptations.
  • 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_69da62636cc08190982cc71733a17b8d completed April 11, 2026, 3:01 p.m.
NER Named-entity recognition batch_69e6673ab4e08190b76ec742605e103b completed April 20, 2026, 5:49 p.m.
Created at: April 11, 2026, 11:30 p.m.