Triple

T7357094
Position Surface form Disambiguated ID Type / Status
Subject She's All That E169652 entity
Predicate portrayedBy P1507 FINISHED
Object Paul Walker E242242 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: Paul Walker | Statement: [She's All That, portrayedBy, Paul Walker]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Paul Walker
Context triple: [She's All That, portrayedBy, Paul Walker]
  • A. Paul Walker
    Paul Walker is a British businessman and former chief executive of the software company Sage Group, known for his leadership in the technology and business sectors.
  • B. Paul Walker chosen
    Paul Walker was an American actor best known for his role as Brian O'Conner in the "Fast & Furious" film franchise.
  • C. Joe Ranft
    Joe Ranft was an influential American storyboard artist, writer, and animator best known for his key creative contributions to numerous Disney and Pixar films.
  • D. Michael Madsen
    Michael Madsen is an American actor known for his tough-guy roles in films such as Reservoir Dogs, Kill Bill, and other Quentin Tarantino movies.
  • E. Vin Diesel
    Vin Diesel is an American actor and producer best known for his role as Dominic Toretto in the Fast & Furious film franchise.
  • 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_69c68a59f2288190877ca15c19b1e822 completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f13a62e48190a2d1781a630aa9f0 completed March 27, 2026, 9:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7faa6a5d88190b969b7783edc67b7 completed March 28, 2026, 3:58 p.m.
Created at: March 27, 2026, 3:06 p.m.