Triple

T17024354
Position Surface form Disambiguated ID Type / Status
Subject Project A E413024 entity
Predicate stars P1956 FINISHED
Object Hark Tsui E544101 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: Hark Tsui | Statement: [Project A, stars, Hark Tsui]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hark Tsui
Context triple: [Project A, stars, Hark Tsui]
  • A. Chow Cheung-fai
    Chow Cheung-fai is a Hong Kong figure known primarily as an alumnus of the prestigious Queen's College secondary school.
  • B. Kar Wai Wong
    Kar Wai Wong is an acclaimed Hong Kong filmmaker known for his visually poetic, emotionally resonant films such as "In the Mood for Love" and "Chungking Express."
  • C. Lok Fu
    Lok Fu is a residential neighborhood and transport hub in Hong Kong known for its public housing estates, shopping centre, and MTR station.
  • D. Lee Ka Lau
    Lee Ka Lau is a Canadian entrepreneur and engineer best known as a co-founder of the graphics chip company ATI Technologies.
  • E. Tsui Hark chosen
    Tsui Hark is a pioneering Hong Kong filmmaker renowned for revolutionizing the action and wuxia genres with his visually inventive, high-energy directing style.
  • 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_69d886cc4170819093deddc7b8b4b6a7 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d5d371148190a60d32a72abec09a completed April 18, 2026, 7:04 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0139ef70208190b26029511e91afb0 completed May 11, 2026, 2:07 a.m.
Created at: April 10, 2026, 5:33 a.m.