Triple

T22803378
Position Surface form Disambiguated ID Type / Status
Subject The Capture E564462 entity
Predicate castMember P1668 FINISHED
Object Ken Leung 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: Ken Leung | Statement: [The Capture, castMember, Ken Leung]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ken Leung
Context triple: [The Capture, castMember, Ken Leung]
  • A. Ken Leung chosen
    Ken Leung is an American actor known for his versatile character roles in film and television, including notable appearances in projects like "Lost," "Rush Hour," and "Star Wars: The Force Awakens."
  • B. Yuen Bun
    Yuen Bun is a Hong Kong film actor and action director known for his work in martial arts and action cinema.
  • C. James Lee Wong
    James Lee Wong is a fictional Chinese-American detective featured in a series of mystery stories and films, notably portrayed by Boris Karloff in several 1930s and 1940s movies.
  • D. David Carradine
    David Carradine was an American actor best known for his role as Kwai Chang Caine in the television series "Kung Fu" and for his prominent appearance in Quentin Tarantino's "Kill Bill" films.
  • E. James Hong
    James Hong is a prolific American character actor and voice actor known for his roles in films like "Big Trouble in Little China," "Blade Runner," and numerous animated features.
  • 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_69e245823f4c8190ade442cdcc2c224a completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f17d5a7c2881909a7aaacddd09f00c completed April 29, 2026, 3:39 a.m.
Created at: April 17, 2026, 3:31 p.m.