Triple

T2478807
Position Surface form Disambiguated ID Type / Status
Subject Lady in the Dark E55154 entity
Predicate filmAdaptationDirector P255 FINISHED
Object Mitchell Leisen E37378 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 Leisen | Statement: [Lady in the Dark, filmAdaptationDirector, Mitchell Leisen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mitchell Leisen
Context triple: [Lady in the Dark, filmAdaptationDirector, Mitchell Leisen]
  • A. Mitchell Leisen chosen
    Mitchell Leisen was an American film director, art director, and costume designer known for his stylish Hollywood productions from the 1930s and 1940s.
  • B. Andrew Miano
    Andrew Miano is an American film producer known for his work on independent and critically acclaimed movies, often collaborating with director Tom Ford and others.
  • C. Darius Ogden Mills
    Darius Ogden Mills was a prominent 19th-century American banker, financier, and philanthropist influential in the development of California.
  • D. Kevin Yagher
    Kevin Yagher is an American special effects and makeup artist and director best known for his work on horror and fantasy films and for creating iconic genre characters.
  • E. Joseph Weishaar
    Joseph Weishaar is an American architect and designer best known for winning the competition to create the National World War I Memorial in Washington, D.C.
  • 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_69ab49e279e88190ab10d7248aea9d11 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abd15f95888190a94b5fef7fdf1bcb completed March 7, 2026, 7:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69afa0425944819096e87fadfce94bc2 completed March 10, 2026, 4:38 a.m.
Created at: March 6, 2026, 9:45 p.m.