Triple

T5764439
Position Surface form Disambiguated ID Type / Status
Subject The Fast and the Furious: Tokyo Drift E127174 entity
Predicate stars P1956 FINISHED
Object Sung Kang E268557 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: Sung Kang | Statement: [The Fast and the Furious: Tokyo Drift, stars, Sung Kang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sung Kang
Context triple: [The Fast and the Furious: Tokyo Drift, stars, Sung Kang]
  • A. Sung Kang chosen
    Sung Kang is an American actor best known for his role as Han Lue in the Fast & Furious film franchise.
  • B. Il-woo Jung
    Il-woo Jung is a Korean individual notable enough to be recognized as a prominent bearer of the surname Jung.
  • C. John Cho
    John Cho is a Korean American actor best known for his roles in the "Harold & Kumar" comedy series and as Hikaru Sulu in the rebooted "Star Trek" film franchise.
  • D. Haan Lee
    Haan Lee is one of the children of acclaimed Taiwanese-American film director Ang Lee.
  • E. Peter Sohn
    Peter Sohn is an American animator, voice actor, and film director at Pixar known for his work on projects like "Ratatouille," "The Good Dinosaur," and "Elemental."
  • 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_69c00833a3fc81908f4bc29ed011b7a6 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c0296e12d48190bd120879723bb6e8 completed March 22, 2026, 5:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69c07e59c2d0819091101dea300e1d7e completed March 22, 2026, 11:42 p.m.
Created at: March 22, 2026, 3:49 p.m.