Triple

T17748669
Position Surface form Disambiguated ID Type / Status
Subject Ken Lo E443053 entity
Predicate name P16 FINISHED
Object Ken Lo 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 Lo | Statement: [Ken Lo, name, Ken Lo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ken Lo
Context triple: [Ken Lo, name, Ken Lo]
  • A. Ken Lo chosen
    Ken Lo is a Hong Kong-based martial artist and actor best known for his action and stunt work in films such as Jackie Chan’s "Drunken Master II."
  • B. Kim Jee-woon
    Kim Jee-woon is a South Korean film director and screenwriter known for his stylish, genre-spanning works such as "A Tale of Two Sisters," "A Bittersweet Life," and "I Saw the Devil."
  • C. Hwang Jang-lee
    Hwang Jang-lee is a Korean martial artist and actor famed for his villainous kicking roles in classic Hong Kong kung fu films.
  • D. Kim Ki-young
    Kim Ki-young was a pioneering South Korean film director best known for his psychologically intense, genre-blending works such as "The Housemaid," which deeply influenced later auteurs like Bong Joon-ho.
  • E. Na Hong-jin
    Na Hong-jin is a South Korean filmmaker renowned for his intense, genre-blending thrillers such as "The Chaser," "The Yellow Sea," and "The Wailing."
  • 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_69e47ad46a50819089c87f74efe3c7ca completed April 19, 2026, 6:48 a.m.
Created at: April 10, 2026, 10:10 a.m.