Triple

T5764446
Position Surface form Disambiguated ID Type / Status
Subject The Fast and the Furious: Tokyo Drift E127174 entity
Predicate featuresCharacter P626 FINISHED
Object Takashi E293865 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: Takashi | Statement: [The Fast and the Furious: Tokyo Drift, featuresCharacter, Takashi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Takashi
Context triple: [The Fast and the Furious: Tokyo Drift, featuresCharacter, Takashi]
  • A. Takashi chosen
    Takashi is a Japanese given name commonly used for males and borne by numerous notable figures in fields such as arts, sports, and entertainment.
  • B. Taisuke
    Taisuke is a Japanese given name notably borne by historical figures such as the Meiji-era politician Itagaki Taisuke.
  • C. Tadahiko
    Tadahiko is a Japanese masculine given name used by various notable individuals in fields such as sports, arts, and academia.
  • D. Takeharu
    Takeharu is a Japanese given name commonly used for males.
  • E. Takahito
    Takahito, better known by his title Prince Mikasa, was a member of the Japanese imperial family and the youngest son of Emperor Taishō.
  • 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_69c0a16ea7108190adb0756dac94c42c completed March 23, 2026, 2:11 a.m.
Created at: March 22, 2026, 3:49 p.m.