Triple

T6142344
Position Surface form Disambiguated ID Type / Status
Subject Beth Riesgraf E136990 entity
Predicate portrayed P1668 FINISHED
Object Parker E44427 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: Parker | Statement: [Beth Riesgraf, portrayed, Parker]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Parker
Context triple: [Beth Riesgraf, portrayed, Parker]
  • A. Parker
    Parker is a 2013 American crime thriller film starring Jason Statham as a professional thief who seeks revenge after being double-crossed by his crew.
  • B. Parker chosen
    Parker is a common English surname borne by numerous notable individuals across fields such as politics, sports, arts, and science.
  • C. Tucker
    Tucker is a surname most notably associated with Albert W. Tucker, a Canadian-American mathematician and game theorist known for his contributions to topology and the formalization of the prisoner's dilemma.
  • D. Spencer
    Spencer is a masculine given name of English origin, historically associated with roles such as steward or dispenser and borne by various notable figures.
  • E. Spencer
    Spencer is a 2021 biographical psychological drama film depicting Princess Diana during a tense Christmas holiday with the British royal family, starring Kristen Stewart in the lead role.
  • 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_69c008a2c6308190a56519b22d55d083 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c05cb387ac8190a60579b59a741425 completed March 22, 2026, 9:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69c141777d808190ad36b574356ca715 completed March 23, 2026, 1:34 p.m.
Created at: March 22, 2026, 4:16 p.m.