Triple

T17749184
Position Surface form Disambiguated ID Type / Status
Subject To Live E443068 entity
Predicate castMember P1668 FINISHED
Object Jiang Wu 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: Jiang Wu | Statement: [To Live, castMember, Jiang Wu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jiang Wu
Context triple: [To Live, castMember, Jiang Wu]
  • A. Jiang Wu chosen
    Jiang Wu is a Chinese actor known for his roles in both mainstream and art-house films, often portraying intense and complex characters.
  • B. Jiang Wan
    Jiang Wan was a prominent statesman and regent of the Shu Han kingdom during China’s Three Kingdoms period, known for succeeding Zhuge Liang in overseeing state affairs.
  • C. Jiang Baili
    Jiang Baili was a prominent early 20th-century Chinese military strategist and reformer who played a key role in modernizing China's armed forces and influencing Republican-era military thought.
  • D. Liang Congjie
    Liang Congjie was a prominent Chinese historian and environmental activist who founded Friends of Nature, one of China’s first environmental NGOs.
  • E. Luo Jin
    Luo Jin is a Chinese actor known for his roles in popular television dramas and films.
  • 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.