Triple

T15691995
Position Surface form Disambiguated ID Type / Status
Subject Elle Driver E380352 entity
Predicate trainedBy P3665 FINISHED
Object Pai Mei E528808 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: Pai Mei | Statement: [Elle Driver, trainedBy, Pai Mei]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pai Mei
Context triple: [Elle Driver, trainedBy, Pai Mei]
  • A. Pai Mei chosen
    Pai Mei is a legendary, ruthless martial arts master in Quentin Tarantino’s Kill Bill saga, known for his brutal training methods and near-mythic fighting skills.
  • B. Sihung Lung
    Sihung Lung was a Taiwanese actor best known for his frequent collaborations with director Ang Lee, often portraying dignified patriarchal figures in acclaimed films.
  • C. Hikong K’fo-i
    Hikong K’fo-i is one of the scenic waterfalls within the Lake Sebu area in South Cotabato, Philippines, known for its natural beauty and cultural significance to the T’boli people.
  • D. Liu-kung Tao
    Liu-kung Tao is an island off the coast of Shandong, China, historically significant as a naval base and site of key events in the First Sino-Japanese War.
  • E. Sensei Wu
    Sensei Wu is a wise, elderly ninja master from the Lego Ninjago franchise who mentors the main ninja heroes in their battles against evil.
  • 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_69d86d99e860819094b6957cde470f2c completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e04f4f5a888190bd3681bcb9bbc02f completed April 16, 2026, 2:54 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff6eebaccc8190a61fb2f9b9bdbcc1 completed May 9, 2026, 5:29 p.m.
Created at: April 10, 2026, 4:44 a.m.