Triple

T18518453
Position Surface form Disambiguated ID Type / Status
Subject Cinderella (ballet) E452524 entity
Predicate subject P450 FINISHED
Object Prince Charming 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: Prince Charming | Statement: [Cinderella (ballet), subject, Prince Charming]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Prince Charming
Context triple: [Cinderella (ballet), subject, Prince Charming]
  • A. Prince Charming chosen
    Prince Charming is the idealized fairytale prince known for rescuing and marrying Cinderella in the classic Disney story.
  • B. Prince Hans
    Prince Hans is the charming yet treacherous antagonist from Disney's Frozen, who deceitfully schemes to seize control of the kingdom of Arendelle.
  • C. Prince Eric
    Prince Eric is the brave and kind-hearted human prince who becomes Ariel’s love interest in Disney’s animated film "The Little Mermaid."
  • D. Prince Humperdinck
    Prince Humperdinck is the scheming, cowardly prince and primary antagonist in the fantasy romance film and novel "The Princess Bride."
  • E. The Grand Duke (Disney's "Cinderella")
    The Grand Duke in Disney's "Cinderella" is the King’s fussy, long-suffering advisor tasked with organizing the royal ball and later tracking down the mysterious girl who captured the Prince’s heart.
  • 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_69d8d386df84819092355ebb260d848e completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e5338be20c8190bc7fe8de050345a2 completed April 19, 2026, 7:57 p.m.
Created at: April 10, 2026, 11:36 a.m.