Triple

T3290125
Position Surface form Disambiguated ID Type / Status
Subject Joaquim de Almeida E69079 entity
Predicate notableWork P4 FINISHED
Object Fast Five E268559 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: Fast Five | Statement: [Joaquim de Almeida, notableWork, Fast Five]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fast Five
Context triple: [Joaquim de Almeida, notableWork, Fast Five]
  • A. Fast Five chosen
    Fast Five is a 2011 action film in the Fast & Furious franchise that shifts the series toward heist-centered storytelling and ensemble ensemble action set pieces.
  • B. Fast & Furious
    Fast & Furious is a blockbuster action film franchise centered on high-speed street racing, elaborate heists, and a tight-knit crew that treats each other like family.
  • C. The Fast and the Furious: Tokyo Drift
    The Fast and the Furious: Tokyo Drift is a 2006 action film in the Fast & Furious franchise that centers on underground drift racing culture in Tokyo, Japan.
  • D. Furious 7
    Furious 7 is a 2015 action film in the Fast & Furious franchise, known for its high-octane stunts and serving as Paul Walker’s final appearance in the series.
  • E. Gone in 60 Seconds
    Gone in 60 Seconds is a high-octane heist film centered on a retired car thief forced to steal dozens of luxury vehicles in one night to save his brother’s life.
  • 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_69ad859d45748190b0742408c954b39f completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb05bd6b08190bcb9f0e5da82bc21 completed March 8, 2026, 5:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69b2e862835881909c2f3b8f86f10742 completed March 12, 2026, 4:22 p.m.
Created at: March 8, 2026, 3:10 p.m.