Triple

T6142336
Position Surface form Disambiguated ID Type / Status
Subject Beth Riesgraf E136990 entity
Predicate name P16 FINISHED
Object Beth Riesgraf E136990 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: Beth Riesgraf | Statement: [Beth Riesgraf, name, Beth Riesgraf]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Beth Riesgraf
Context triple: [Beth Riesgraf, name, Beth Riesgraf]
  • A. Beth Riesgraf chosen
    Beth Riesgraf is an American actress best known for playing the quirky thief Parker on the television series "Leverage."
  • B. Rhea Seehorn
    Rhea Seehorn is an American actress best known for her critically acclaimed role as attorney Kim Wexler on the television series "Better Call Saul."
  • C. Lily Rabe
    Lily Rabe is an American actress known for her versatile performances in film, television, and theater, particularly for her recurring roles in the anthology series "American Horror Story."
  • D. Caissie Levy
    Caissie Levy is a Canadian stage actress and singer best known for her leading roles in major Broadway and West End musicals, including originating Elsa in Disney’s Frozen on Broadway.
  • E. Lynn Collins
    Lynn Collins is an American actress known for her roles in films such as X-Men Origins: Wolverine and John Carter, as well as various television series.
  • 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_69c64b9dc6d08190919aa58e05c25635 completed March 27, 2026, 9:19 a.m.
Created at: March 22, 2026, 4:16 p.m.