Triple

T18181844
Position Surface form Disambiguated ID Type / Status
Subject Kai Wasikowska E435305 entity
Predicate notableRelative P367 FINISHED
Object Mia Wasikowska NE NERFINISHED

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: Mia Wasikowska | Statement: [Kai Wasikowska, notableRelative, Mia Wasikowska]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mia Wasikowska
Context triple: [Kai Wasikowska, notableRelative, Mia Wasikowska]
  • A. Mia Wasikowska chosen
    Mia Wasikowska is an Australian actress known for her versatile performances in films such as "Alice in Wonderland," "Jane Eyre," and various independent dramas.
  • B. Jess Wasikowska
    Jess Wasikowska is a sibling of Australian actress Mia Wasikowska, known for her role in films such as "Alice in Wonderland."
  • C. Kai Wasikowska
    Kai Wasikowska is a sibling of Australian actress and filmmaker Mia Wasikowska, known for her roles in independent and mainstream films.
  • D. Marzen Wasikowska
    Marzen Wasikowska is the mother of Australian actress Mia Wasikowska.
  • E. Rooney Mara
    Rooney Mara is an American actress known for her acclaimed performances in films such as "The Girl with the Dragon Tattoo" and "Carol."
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b90c7ec081909b4694ccecb449c6 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4dffb3bc88190a627be9c444d5c7d completed April 19, 2026, 2 p.m.
Created at: April 10, 2026, 10:31 a.m.