Triple

T5736733
Position Surface form Disambiguated ID Type / Status
Subject Samantha Barks E126519 entity
Predicate portrayed P1668 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: [Samantha Barks, portrayed, Elsa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Elsa
Context triple: [Samantha Barks, portrayed, 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. 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.
  • C. 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.
  • D. Helga
    Helga is a feminine given name of Germanic origin, commonly used in German-speaking and Scandinavian countries.
  • E. Elin
    Elin is a feminine given name, commonly used in Scandinavian countries and often considered a variant of Ellen or Helen.
  • 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_69c0083082288190b7478cead6b5430a completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c0255ad6f48190977bf4f037110aa3 completed March 22, 2026, 5:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69c07e0b871c8190bf8dd0e076bb9789 completed March 22, 2026, 11:40 p.m.
Created at: March 22, 2026, 3:47 p.m.