Triple

T3249111
Position Surface form Disambiguated ID Type / Status
Subject Sleeping Beauty E68133 entity
Predicate protagonist P268 FINISHED
Object Princess Aurora E228070 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: Princess Aurora | Statement: [Sleeping Beauty, protagonist, Princess Aurora]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Princess Aurora
Context triple: [Sleeping Beauty, protagonist, Princess Aurora]
  • A. Princess Fiona
    Princess Fiona is a strong-willed, ogre-cursed princess from the Shrek film series who subverts traditional fairy-tale stereotypes.
  • B. Lilac Fairy chosen
    The Lilac Fairy is a benevolent and powerful fairy in Tchaikovsky’s ballet "The Sleeping Beauty," who protects Princess Aurora and ultimately guides her to a happy awakening.
  • C. Drizella Tremaine
    Drizella Tremaine is one of Cinderella’s vain and spiteful stepsisters in Disney’s Cinderella, known for her jealousy, cruelty, and comic incompetence.
  • D. Sleeping Beauty
    Sleeping Beauty is a classic 1959 animated fantasy film from Disney, renowned for its stylized art, iconic villain Maleficent, and the story of Princess Aurora cursed into a magical sleep.
  • E. Rapunzel
    Rapunzel is a classic fairy-tale princess best known for her extraordinarily long hair and her story of captivity in a tower and eventual escape.
  • 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_69ad858e4c708190aa31d486cfee8a6a completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69adaf3fc3c8819080ac95974581ca0e completed March 8, 2026, 5:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69b2f3be35388190bbd1a296d7b1b3fa completed March 12, 2026, 5:11 p.m.
Created at: March 8, 2026, 3:09 p.m.