Triple

T20882816
Position Surface form Disambiguated ID Type / Status
Subject Desk Set E514195 entity
Predicate director P255 FINISHED
Object Walter Lang 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: Walter Lang | Statement: [Desk Set, director, Walter Lang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Walter Lang
Context triple: [Desk Set, director, Walter Lang]
  • A. Walter Lang chosen
    Walter Lang was an American film director best known for his work on classic Hollywood musicals and comedies during the 1930s–1950s.
  • B. George Sidney
    George Sidney was an American film director best known for his lavish MGM musicals and comedies during Hollywood’s Golden Age, including classics like "Anchors Aweigh" and "Show Boat."
  • C. George Sidney
    George Sidney was an American actor best known for his work in early 20th-century film comedies and vaudeville-style productions.
  • D. Mervyn LeRoy
    Mervyn LeRoy was an American film director and producer known for his influential work in classic Hollywood cinema, including a key role in bringing "The Wizard of Oz" to the screen.
  • E. Leo McCarey
    Leo McCarey was an American film director, screenwriter, and producer best known for his influential work in both comedy and drama during Hollywood’s Golden Age, including classics like "The Awful Truth" and "Going My Way."
  • 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_69e0b4f733f081908a401c0b7beb0b9f completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c67b03088190be7cbcde8c59509a completed April 21, 2026, 12:36 a.m.
Created at: April 16, 2026, 12:46 p.m.