Triple

T12393914
Position Surface form Disambiguated ID Type / Status
Subject His New Job E296066 entity
Predicate starring P1507 FINISHED
Object Leo White E103723 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: Leo White | Statement: [His New Job, starring, Leo White]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Leo White
Context triple: [His New Job, starring, Leo White]
  • A. Leo White chosen
    Leo White was a British-born American character actor and director best known for his work in silent films, including frequent collaborations with Charlie Chaplin.
  • B. Bibb Falk
    Bibb Falk was an American baseball player and longtime University of Texas coach known for leading the Longhorns to multiple national championships and having the school's baseball stadium named in his honor.
  • C. Gil Doud
    Gil Doud was an American screenwriter best known for his work on mid-20th-century Hollywood films, particularly war and action dramas.
  • D. Hans Conried
    Hans Conried was an American character actor and voice actor best known for his comedic and often villainous roles in mid-20th-century film, radio, television, and animation.
  • E. M. Emmet Walsh
    M. Emmet Walsh is an American character actor known for his prolific film and television career, including memorable roles in movies like "Blade Runner," "Blood Simple," and "Raising Arizona."
  • 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_69d6ad9e653c8190b1473c860ee53dae completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d93fd228488190b216abd1c341563c completed April 10, 2026, 6:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69f63efa1520819093cdf6ab3025ab20 completed May 2, 2026, 6:14 p.m.
Created at: April 8, 2026, 9:54 p.m.