Triple

T9578547
Position Surface form Disambiguated ID Type / Status
Subject Training Day (TV series) E231109 entity
Predicate portrayedBy P1507 FINISHED
Object Bill Paxton E81453 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: Bill Paxton | Statement: [Training Day (TV series), portrayedBy, Bill Paxton]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bill Paxton
Context triple: [Training Day (TV series), portrayedBy, Bill Paxton]
  • A. Bill Paxton chosen
    Bill Paxton was an American actor and filmmaker known for his versatile roles in films such as "Aliens," "Twister," "Titanic," and "Apollo 13."
  • B. Jeff Bridges
    Jeff Bridges is an acclaimed American actor known for his versatile performances in films such as "The Big Lebowski," "Crazy Heart," and "True Grit."
  • C. John Goodman
    John Goodman is an American actor known for his roles in the sitcom "Roseanne," numerous Coen brothers films, and for voicing Sulley in Pixar's "Monsters, Inc." franchise.
  • D. Danny Glover
    Danny Glover is an American actor and activist best known for his roles in films such as the "Lethal Weapon" series and "The Color Purple."
  • E. Gil Bellows
    Gil Bellows is a Canadian actor best known for his roles in films like The Shawshank Redemption and the television series Ally McBeal.
  • 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_69ca848091c48190bc313d6620d09555 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd99aece1081908287e03106de020f completed April 1, 2026, 10:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1615d093c8190940037e9e0842db5 completed April 4, 2026, 7:07 p.m.
Created at: March 30, 2026, 8:05 p.m.