Triple

T5042955
Position Surface form Disambiguated ID Type / Status
Subject The Final Option E113587 entity
Predicate stars P1956 FINISHED
Object Judy Davis E124310 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: Judy Davis | Statement: [The Final Option, stars, Judy Davis]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Judy Davis
Context triple: [The Final Option, stars, Judy Davis]
  • A. Judy Davis chosen
    Judy Davis is an acclaimed Australian actress known for her intense, nuanced performances in film, television, and theatre, and for collaborations with directors such as Gillian Armstrong and Woody Allen.
  • B. Holly Hunter
    Holly Hunter is an Academy Award–winning American actress known for her intense, nuanced performances in films such as "The Piano," "Broadcast News," and "Raising Arizona."
  • C. Jacki Weaver
    Jacki Weaver is an Australian actress acclaimed for her work in film, television, and theatre, including her Oscar-nominated performance in "Silver Linings Playbook."
  • D. Shirley Henderson
    Shirley Henderson is a Scottish actress known for her distinctive voice and roles in films such as the Bridget Jones series and the Harry Potter franchise.
  • E. Jacqueline Bisset
    Jacqueline Bisset is an English actress known for her work in films from the 1960s onward, including prominent roles in both European and Hollywood cinema.
  • 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_69bd44391fc48190a311ce9c826c209b completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd73df8f7481909a8b86c4ae69aab9 completed March 20, 2026, 4:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69be9c87455081908b759eed55730503 completed March 21, 2026, 1:26 p.m.
Created at: March 20, 2026, 1:37 p.m.