Triple

T3653246
Position Surface form Disambiguated ID Type / Status
Subject Bad Times at the El Royale E77469 entity
Predicate castMember P1668 FINISHED
Object Jeff Bridges E101127 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: Jeff Bridges | Statement: [Bad Times at the El Royale, castMember, Jeff Bridges]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jeff Bridges
Context triple: [Bad Times at the El Royale, castMember, Jeff Bridges]
  • A. Jeff Bridges chosen
    Jeff Bridges is an acclaimed American actor known for his versatile performances in films such as "The Big Lebowski," "Crazy Heart," and "True Grit."
  • B. Gene Hackman
    Gene Hackman is an acclaimed American actor known for his powerful, versatile performances in films such as "The French Connection," "The Conversation," and "Unforgiven."
  • C. Bill Paxton
    Bill Paxton was an American actor and filmmaker known for his versatile roles in films such as "Aliens," "Twister," "Titanic," and "Apollo 13."
  • D. Ned Beatty
    Ned Beatty was an acclaimed American character actor known for his powerful supporting roles in films such as "Deliverance," "Network," and "Superman."
  • E. Kurt Russell
    Kurt Russell is an American actor known for his versatile performances in films ranging from action and science fiction to drama and comedy, including iconic roles in movies like "Escape from New York," "The Thing," and "Tombstone."
  • 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_69ad85def5cc8190863dccf55a18bebb completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc3b805a48190a7bc230a382365d6 completed March 8, 2026, 6:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69b488394aa48190b91985aa912cf733 completed March 13, 2026, 9:57 p.m.
Created at: March 8, 2026, 3:24 p.m.