Triple

T11050499
Position Surface form Disambiguated ID Type / Status
Subject Empire Award for Best Actor E261232 entity
Predicate hasNotableRecipient P108 FINISHED
Object Tom Cruise E138735 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: Tom Cruise | Statement: [Empire Award for Best Actor, hasNotableRecipient, Tom Cruise]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tom Cruise
Context triple: [Empire Award for Best Actor, hasNotableRecipient, Tom Cruise]
  • A. Tom Cruise chosen
    Tom Cruise is an American actor and producer renowned for his charismatic performances in blockbuster action and science-fiction films, including the Mission: Impossible series and numerous critically acclaimed roles.
  • B. Brad Pitt
    Brad Pitt is an American actor and film producer renowned for his leading roles in major Hollywood films and for winning multiple Academy Awards.
  • C. Scott Anthony Redford
    Scott Anthony Redford is one of the children of acclaimed American actor and filmmaker Robert Redford.
  • D. Nicolas Cage
    Nicolas Cage is an American actor known for his intense and eclectic performances across action, drama, and independent films.
  • E. Richard Gere
    Richard Gere is an American actor known for his leading roles in films such as "American Gigolo," "An Officer and a Gentleman," and "Pretty Woman."
  • 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_69d6aa98650481908609c7c56bfa7902 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d79868c78881908c8e3672c05ae7ec completed April 9, 2026, 12:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69e3aa146b148190a87205e542cc718f completed April 18, 2026, 3:58 p.m.
Created at: April 8, 2026, 9:26 p.m.