Triple

T5143289
Position Surface form Disambiguated ID Type / Status
Subject John Connor E116010 entity
Predicate portrayedBy P1507 FINISHED
Object Jason Clarke E15309 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: Jason Clarke | Statement: [John Connor, portrayedBy, Jason Clarke]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jason Clarke
Context triple: [John Connor, portrayedBy, Jason Clarke]
  • A. Jason Clarke chosen
    Jason Clarke is an Australian actor known for his intense performances in films such as "Zero Dark Thirty," "Dawn of the Planet of the Apes," and "Chappaquiddick."
  • B. Ben Foster
    Ben Foster is an American actor known for his intense, often gritty performances in films such as "3:10 to Yuma," "Hell or High Water," and "The Messenger."
  • C. Ben Foster
    Ben Foster is a British composer and orchestrator best known for his work on television scores, including contributions to the revived Doctor Who series.
  • D. Frank Grillo
    Frank Grillo is an American actor best known for his tough, action-oriented roles in films such as the Purge series and the Marvel Cinematic Universe.
  • E. Jeremy Renner
    Jeremy Renner is an American actor and musician best known for his roles in films such as "The Hurt Locker" and as Hawkeye in the Marvel Cinematic Universe.
  • 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_69bd4446c0e08190a7c29dc74976bf03 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd7883004881909c763da818d9b6e2 completed March 20, 2026, 4:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69becfec5c108190a3882c25118179a7 completed March 21, 2026, 5:05 p.m.
Created at: March 20, 2026, 1:43 p.m.