Triple

T5914245
Position Surface form Disambiguated ID Type / Status
Subject Cuts E131537 entity
Predicate characterRole P268 FINISHED
Object Shannon Elizabeth as Tiffany Sherwood E23613 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: Shannon Elizabeth as Tiffany Sherwood | Statement: [Cuts, characterRole, Shannon Elizabeth as Tiffany Sherwood]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Shannon Elizabeth as Tiffany Sherwood
Context triple: [Cuts, characterRole, Shannon Elizabeth as Tiffany Sherwood]
  • A. Shannon Elizabeth chosen
    Shannon Elizabeth is an American actress and former fashion model best known for her breakout role in the comedy film "American Pie."
  • B. Laura Innes
    Laura Innes is an American actress and television director best known for her long-running role as Dr. Kerry Weaver on the medical drama series "ER."
  • C. Victoria Knox – Jessica Alba
    Victoria Knox is the ruthless and cunning arms dealer portrayed by Jessica Alba in the action-comedy film "Barely Lethal."
  • D. Nikki Reed
    Nikki Reed is an American actress and screenwriter best known for her role as Rosalie Hale in the Twilight film series.
  • E. Gina Torres
    Gina Torres is an American actress known for her roles in television series such as "Suits," "Firefly," and "Hannibal."
  • 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_69c008593a44819081a07ae0efe6c574 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c037b9f0908190ad854e5f2600f114 completed March 22, 2026, 6:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0c02430bc8190a63b91b6dbdbc9f2 completed March 23, 2026, 4:23 a.m.
Created at: March 22, 2026, 3:59 p.m.