Triple

T14411761
Position Surface form Disambiguated ID Type / Status
Subject Blancanieves E357344 entity
Predicate basedOn P98 FINISHED
Object Snow White E632975 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: Snow White | Statement: [Blancanieves, basedOn, Snow White]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Snow White
Context triple: [Blancanieves, basedOn, Snow White]
  • A. Snow White chosen
    Snow White is the kind-hearted princess and central heroine of Disney’s classic 1937 animated film "Snow White and the Seven Dwarfs," renowned as the studio’s first feature-length animated character.
  • B. Princess Aurora
    Princess Aurora is the kind-hearted, golden-haired princess from Disney’s Sleeping Beauty, known for her enchanted slumber and her central role in the reimagined Maleficent films.
  • C. Snowy White
    Snowy White is a British blues and rock guitarist known for his work with Thin Lizzy, Pink Floyd-related projects, and his own solo career.
  • D. Snow Queen
    "Snow Queen" is a lesser-known 1976 pop song by Elton John and Kiki Dee, released as the B-side to their hit duet "Don't Go Breaking My Heart."
  • E. Cinderella
    Cinderella is a musical by Andrew Lloyd Webber that reimagines the classic fairy tale with a modern twist in story, character, and score.
  • 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_69d82793421c8190861eb0e673b085de completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de90c9b3448190aec1608836a5e913 completed April 14, 2026, 7:08 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd55269d8c81909592277741a93db6 completed May 8, 2026, 3:14 a.m.
Created at: April 10, 2026, 1:17 a.m.