Triple

T6991997
Position Surface form Disambiguated ID Type / Status
Subject Disney animated universe E162105 entity
Predicate notableCharacter P1481 FINISHED
Object Elsa E44923 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: Elsa | Statement: [Disney animated universe, notableCharacter, Elsa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Elsa
Context triple: [Disney animated universe, notableCharacter, Elsa]
  • A. Elsa chosen
    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."
  • B. Elsa Viveca Torstensdotter Lindfors
    Elsa Viveca Torstensdotter Lindfors, known professionally as Viveca Lindfors, was a Swedish-American actress celebrated for her work in European and Hollywood films and on stage during the mid-20th century.
  • C. Anna and Elsa
    Anna and Elsa are the popular sister protagonists from Disney's animated film "Frozen," known for their roles as the Snow Queen and the princess of Arendelle.
  • D. 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.
  • E. Helga
    Helga is a feminine given name of Germanic origin, commonly used in German-speaking and Scandinavian countries.
  • 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_69c68856d7808190ab33ee914640281b completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6dbc1f63c8190837cfd71cf5ed613 completed March 27, 2026, 7:34 p.m.
NED1 Entity disambiguation (via context triple) batch_69c761d6ed5481909ccf1650fe6dc747 completed March 28, 2026, 5:06 a.m.
Created at: March 27, 2026, 2:32 p.m.