Triple

T2461715
Position Surface form Disambiguated ID Type / Status
Subject Fast & Furious E54547 entity
Predicate featuresCharacter P626 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, featuresCharacter, Tej Parker]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tej Parker
Context triple: [Fast & Furious, featuresCharacter, 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. Jennifer Parker
    Jennifer Parker is Marty McFly’s girlfriend in the Back to the Future film series, appearing as a key supporting character across its time-travel adventures.
  • D. Tiana Rogers
    Tiana Rogers was a Cherokee woman known for her marriage to Sam Houston, the American statesman and leader of the Republic of Texas.
  • E. Greer Shephard
    Greer Shephard is an American television producer and director best known for co-creating and producing acclaimed drama series such as Nip/Tuck and The Closer.
  • 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_69ab49dee84c819096b50a0049c347ac completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abd11c47408190b10c7f6a151f2db2 completed March 7, 2026, 7:17 a.m.
NED1 Entity disambiguation (via context triple) batch_69aef0d2b2748190b12611863d8bf4ad completed March 9, 2026, 4:09 p.m.
Created at: March 6, 2026, 9:44 p.m.