Triple

T22940600
Position Surface form Disambiguated ID Type / Status
Subject Nikki Satosky E569716 entity
Predicate portrayedBy P1507 FINISHED
Object Mara Wilson 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: Mara Wilson | Statement: [Nikki Satosky, portrayedBy, Mara Wilson]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mara Wilson
Context triple: [Nikki Satosky, portrayedBy, Mara Wilson]
  • A. Mara Wilson chosen
    Mara Wilson is an American former child actress and writer best known for her roles in films like "Matilda," "Mrs. Doubtfire," and "Miracle on 34th Street."
  • B. Tali David
    Tali David is a minor character in the TV series "NCIS," known as the younger sister of main character Ziva David.
  • C. Tali Pelman
    Tali Pelman is a theatre producer known for her work on major West End productions, including the 2013 staging of "Mojo."
  • D. Maya Ford
    Maya Ford is an American musician best known as the bassist for the all-female rock band The Donnas.
  • E. Rachel Zane
    Rachel Zane is a central character in the legal drama series "Suits," known as a talented paralegal who aspires to become a lawyer and develops a key romantic relationship with Mike Ross.
  • 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_69e24590862c8190858f180ad302adab completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f1813844b88190b05d3829b0c423c4 completed April 29, 2026, 3:55 a.m.
Created at: April 17, 2026, 3:45 p.m.