Triple

T13700999
Position Surface form Disambiguated ID Type / Status
Subject To Wong Foo, Thanks for Everything! Julie Newmar E328516 entity
Predicate writer P1360 FINISHED
Object Douglas Carter Beane E1055684 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: Douglas Carter Beane | Statement: [To Wong Foo, Thanks for Everything! Julie Newmar, writer, Douglas Carter Beane]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Douglas Carter Beane
Context triple: [To Wong Foo, Thanks for Everything! Julie Newmar, writer, Douglas Carter Beane]
  • A. Douglas Carter Beane chosen
    Douglas Carter Beane is an American playwright and screenwriter known for his sharp wit and work on stage and screen, including acclaimed plays and Broadway musicals.
  • B. Don Beyer
    Don Beyer is an American Democratic politician and former Lieutenant Governor of Virginia who serves in the U.S. House of Representatives.
  • C. Charles Beahan
    Charles Beahan was an American screenwriter best known for his work on early 20th-century Hollywood films.
  • D. Dennis Berry
    Dennis Berry was an American-born French film director and actor known for his work in European cinema and his marriage to iconic actress Anna Karina.
  • E. Randall Brown
    Randall Brown is a central character in the British television drama series "The Hour," known for his complex, enigmatic role within the show's 1950s newsroom setting.
  • 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_69d8076ff62081908a7bd79889edd7a0 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbc879adc88190b03f1cf815b71061 completed April 12, 2026, 4:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69f79d50f34c8190ac5b4e09ab57baa9 completed May 3, 2026, 7:09 p.m.
Created at: April 9, 2026, 9:54 p.m.