Triple

T18261290
Position Surface form Disambiguated ID Type / Status
Subject Swiss Army Man E437361 entity
Predicate producer P490 FINISHED
Object Jonathan Wang 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: Jonathan Wang | Statement: [Swiss Army Man, producer, Jonathan Wang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jonathan Wang
Context triple: [Swiss Army Man, producer, Jonathan Wang]
  • A. Jonathan Wang chosen
    Jonathan Wang is a film producer best known for his work on the acclaimed, genre-bending movie "Everything Everywhere All at Once."
  • B. Edward Wang
    Edward Wang is an entrepreneur best known as a founder of the virtualization and cloud computing company VMware.
  • C. William Wang
    William Wang is a Taiwanese-American entrepreneur best known as the founder and longtime CEO of the consumer electronics company Vizio.
  • D. Peter Wang
    Peter Wang was a Taiwanese-American actor and filmmaker best known for his role in the influential Asian American independent film "Chan Is Missing."
  • E. Jason Wong
    Jason Wong is a British actor known for his roles in film and television, including his appearance in Guy Ritchie's crime-comedy series "The Gentlemen."
  • 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_69d8b913351c8190932b6a426de04b41 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4ff76a1208190abbe6ab8720ed154 completed April 19, 2026, 4:14 p.m.
Created at: April 10, 2026, 10:34 a.m.