Triple

T18958947
Position Surface form Disambiguated ID Type / Status
Subject Who Was That Lady? E463857 entity
Predicate director P255 FINISHED
Object George Sidney 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: George Sidney | Statement: [Who Was That Lady?, director, George Sidney]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: George Sidney
Context triple: [Who Was That Lady?, director, George Sidney]
  • A. George Sidney chosen
    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."
  • B. George Sidney
    George Sidney was an American actor best known for his work in early 20th-century film comedies and vaudeville-style productions.
  • C. 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.
  • D. Charles Vidor
    Charles Vidor was a Hungarian-American film director best known for classic Hollywood movies such as "Gilda" and other major studio productions of the 1940s and 1950s.
  • E. Michael Curtiz
    Michael Curtiz was a Hungarian-American film director best known for helming classic Hollywood films such as "Casablanca."
  • 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_69d8dcffc278819086792a4ebfddfafa completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5d5d057a48190b82b5788b3281e28 completed April 20, 2026, 7:29 a.m.
Created at: April 10, 2026, noon