Triple

T2041445
Position Surface form Disambiguated ID Type / Status
Subject The Sleeping Beauty E44753 entity
Predicate notableCharacter P1481 FINISHED
Object Princess Aurora E68133 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: [The Sleeping Beauty, notableCharacter, Princess Aurora]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Princess Aurora
Context triple: [The Sleeping Beauty, notableCharacter, Princess Aurora]
  • A. Sleeping Beauty chosen
    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.
  • B. 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.
  • C. Elsa
    Elsa is a feminine given name of Germanic origin, widely recognized today through its use for the main character in Disney's animated film "Frozen."
  • D. The Evil Queen
    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.
  • E. Princess Yori
    Princess Yori is a fictional royal character, also known as Princess Atsuko, who appears in Japanese-inspired storytelling and media.
  • 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_69a889159ec481908f9e4472d9f480c7 completed March 4, 2026, 7:33 p.m.
NER Named-entity recognition batch_69abb9545aa08190ac74e49e70c4c349 completed March 7, 2026, 5:36 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae1ffbbf948190a89932013b463f85 completed March 9, 2026, 1:18 a.m.
Created at: March 4, 2026, 7:39 p.m.