Triple

T14412286
Position Surface form Disambiguated ID Type / Status
Subject Encarna (Blancanieves) E357358 entity
Predicate basedOn P98 FINISHED
Object Evil Queen E173047 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: Evil Queen | Statement: [Encarna (Blancanieves), basedOn, Evil Queen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Evil Queen
Context triple: [Encarna (Blancanieves), basedOn, Evil Queen]
  • A. The Evil Queen chosen
    The Evil Queen is the vain and power-hungry royal villain from Disney’s Snow White, infamous for her jealousy and use of dark magic to eliminate her rival.
  • B. Carabosse
    Carabosse is the malevolent fairy or sorceress who curses Princess Aurora in the classic fairy tale and ballet "The Sleeping Beauty."
  • C. Queen Red
    Queen Red was one of the designated assault sub-sectors of Sword Beach used by Allied forces during the D-Day landings in World War II.
  • D. Enchantress
    Enchantress is a powerful, ancient sorceress who possesses archaeologist June Moone and serves as one of the primary antagonists in the 2016 superhero film "Suicide Squad."
  • E. the Witch from Rapunzel
    The Witch from Rapunzel is the powerful, overprotective sorceress who imprisons Rapunzel in a tower and serves as the primary antagonist in the classic fairy tale.
  • 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_69de90cb3c708190822f5506ebf7ee9d 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.