Triple

T3993259
Position Surface form Disambiguated ID Type / Status
Subject Everything Everywhere All at Once E87040 entity
Predicate starring P1507 FINISHED
Object James Hong E257352 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: James Hong | Statement: [Everything Everywhere All at Once, starring, James Hong]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: James Hong
Context triple: [Everything Everywhere All at Once, starring, James Hong]
  • A. James Hong chosen
    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.
  • B. Victor Sen Yung
    Victor Sen Yung was a Chinese American character actor best known for his roles as Hop Sing on the television series "Bonanza" and as Jimmy Chan in the Charlie Chan film series.
  • C. Roger Yuan
    Roger Yuan is an American martial artist, fight choreographer, and actor known for his roles and stunt work in numerous action films.
  • D. Lai-Sang Young
    Lai-Sang Young is a prominent mathematician known for her influential work in dynamical systems and ergodic theory.
  • E. Daniel Wu
    Daniel Wu is a Hong Kong-American actor, director, and producer known for his roles in action and fantasy films as well as the TV series "Into the Badlands."
  • 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_69aed94118148190975e6aa4e554cde9 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefa1d9d8c8190982d092a73d38564 completed March 9, 2026, 4:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69b54c50f348819090ebfd8b5192c819 completed March 14, 2026, 11:53 a.m.
Created at: March 9, 2026, 3:33 p.m.