Triple

T15864845
Position Surface form Disambiguated ID Type / Status
Subject Vanessa Zima E384683 entity
Predicate actedIn P1668 FINISHED
Object Wicked E1182059 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: Wicked | Statement: [Vanessa Zima, actedIn, Wicked]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wicked
Context triple: [Vanessa Zima, actedIn, Wicked]
  • A. Wicked
    Wicked is a component or segment of the larger work "Necessary Evil," likely representing a distinct chapter, episode, or storyline within that overarching title.
  • B. Wicked chosen
    Wicked is a 1998 psychological thriller film starring Vanessa Zima as a troubled teenager entangled in murder and obsession.
  • C. WICKED
    WICKED is the powerful and morally ambiguous organization in James Dashner’s Maze Runner series that conducts brutal experiments on teenagers in a desperate attempt to find a cure for a global disease.
  • D. Wicked (musical)
    Wicked is a hit Broadway musical that reimagines the backstory of the witches from "The Wizard of Oz," featuring music and lyrics by Stephen Schwartz and a book by Winnie Holzman.
  • E. Wicked Part One
    Wicked Part One is the first installment of a two-part film adaptation of the hit Broadway musical "Wicked," exploring the untold story of the witches of Oz.
  • 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_69d86da4e86481909f1325fdc971b5ec completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1555e4ee48190a3b27b4ab9bdb1c8 completed April 16, 2026, 9:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffb03ef4e48190abe431e6abc9ef9c completed May 9, 2026, 10:07 p.m.
Created at: April 10, 2026, 4:50 a.m.