Triple

T11339681
Position Surface form Disambiguated ID Type / Status
Subject Fast & Furious 6 E268560 entity
Predicate character P662 FINISHED
Object Tej Parker E248788 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: Tej Parker | Statement: [Fast & Furious 6, character, Tej Parker]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tej Parker
Context triple: [Fast & Furious 6, character, Tej Parker]
  • A. Tej Parker chosen
    Tej Parker is a tech-savvy mechanic and hacker in the Fast & Furious film franchise, known for his intelligence, humor, and close partnership with Roman Pearce.
  • B. Kim Parker
    Kim Parker is a comedic, outspoken teenage character from the sitcom "Moesha," later becoming a central figure in its spin-off series "The Parkers."
  • C. Joy Parker
    Joy Parker was the wife of acclaimed English actor Paul Scofield, with whom she shared a long marriage and family life.
  • D. Christie Parker
    Christie Parker is a fictional character played by actress Jennifer Crystal Foley, best known from her work in American television.
  • E. Carol Parker
    Carol Parker is best known as the wife of Marlon Jackson, a member of the famed Jackson family and former singer of The Jackson 5.
  • 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_69d6aacb1f0881908c84a349fd1be047 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7ea01c6c08190910a6ce8fb7e186d completed April 9, 2026, 6:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69e55645d8bc8190b338c05ee382d5fc completed April 19, 2026, 10:25 p.m.
Created at: April 8, 2026, 9:33 p.m.