Triple

T10215319
Position Surface form Disambiguated ID Type / Status
Subject Margaret E242425 entity
Predicate hasCastMember P2308 FINISHED
Object Olivia Thirlby E11657 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: Olivia Thirlby | Statement: [Margaret, hasCastMember, Olivia Thirlby]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Olivia Thirlby
Context triple: [Margaret, hasCastMember, Olivia Thirlby]
  • A. Olivia Thirlby chosen
    Olivia Thirlby is an American actress known for her roles in films such as "Juno," "Dredd," and various independent and mainstream productions.
  • B. Haley Bennett
    Haley Bennett is an American actress and singer known for her versatile performances in films such as "The Girl on the Train," "The Magnificent Seven," and "Swallow."
  • C. Eliza Scanlen
    Eliza Scanlen is an Australian actress known for her roles in film and television, including prominent performances in projects like "Sharp Objects" and "Little Women."
  • D. Olivia Cooke
    Olivia Cooke is an English actress known for her roles in films like "Ready Player One" and the TV series "Bates Motel" and "House of the Dragon."
  • E. Juno Temple
    Juno Temple is an English actress known for her eclectic film roles and acclaimed performance as Keeley Jones in the television series "Ted Lasso."
  • 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_69d381ae26c48190985abd0e25ee5d04 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d3aa273bdc8190bc4cf67a7923cebc completed April 6, 2026, 12:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69d6a7f6730081908b941eaeb6c00993 completed April 8, 2026, 7:09 p.m.
Created at: April 6, 2026, 11:04 a.m.