Triple

T22425390
Position Surface form Disambiguated ID Type / Status
Subject Kate Capshaw E554353 entity
Predicate notableRelative P367 FINISHED
Object Mikaela Spielberg 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: Mikaela Spielberg | Statement: [Kate Capshaw, notableRelative, Mikaela Spielberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mikaela Spielberg
Context triple: [Kate Capshaw, notableRelative, Mikaela Spielberg]
  • A. Mikaela Spielberg chosen
    Mikaela Spielberg is the adopted daughter of filmmaker Steven Spielberg and actress Kate Capshaw, known for her work in adult entertainment and advocacy around sex work and mental health.
  • B. Daniela Junger
    Daniela Junger is known as the wife of American author and journalist Sebastian Junger.
  • C. Michaela Dietz
    Michaela Dietz is an American voice actress and actress best known for voicing Amethyst in the animated television series "Steven Universe."
  • D. Josie Reitman
    Josie Reitman is the daughter of Canadian-American film director and screenwriter Jason Reitman.
  • E. Michaela Pratt
    Michaela Pratt is a highly ambitious and intelligent law student and later attorney in the TV series "How to Get Away with Murder," known for her drive to succeed and complex moral struggles.
  • 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_69e11e4f2d0c819091aa3558ea2ee630 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15a2d4dd88190a156c24b02b1591b completed April 29, 2026, 1:09 a.m.
Created at: April 16, 2026, 8:47 p.m.