Triple

T17749458
Position Surface form Disambiguated ID Type / Status
Subject Curse of the Golden Flower E443074 entity
Predicate producer P490 FINISHED
Object William Kong 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: William Kong | Statement: [Curse of the Golden Flower, producer, William Kong]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: William Kong
Context triple: [Curse of the Golden Flower, producer, William Kong]
  • A. William Kong chosen
    William Kong is a prominent Hong Kong film producer best known internationally for his work on acclaimed movies such as "Crouching Tiger, Hidden Dragon."
  • B. William Wang
    William Wang is a Taiwanese-American entrepreneur best known as the founder and longtime CEO of the consumer electronics company Vizio.
  • C. Winston Chao
    Winston Chao is a Taiwanese actor best known internationally for his leading role in Ang Lee’s film "The Wedding Banquet" and for portraying historical figure Sun Yat-sen in multiple Chinese-language productions.
  • D. James Kang
    James Kang is a film producer best known for his work on the family martial-arts comedy movie "Three Ninjas."
  • E. Michael Wong
    Michael Wong is a Hong Kong-based actor and singer known for his roles in action and crime films across Asian cinema.
  • 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_69d8b9ed3a2081909b2ec0d4dd2f4c37 completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e48418c0188190beb31809b40e4648 completed April 19, 2026, 7:28 a.m.
Created at: April 10, 2026, 10:10 a.m.