Triple

T2803295
Position Surface form Disambiguated ID Type / Status
Subject Elsa Löwenthal E53994 entity
Predicate givenName P17 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: [Elsa Löwenthal, givenName, Elsa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Elsa
Context triple: [Elsa Löwenthal, givenName, 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. Olaf
    Olaf is a masculine given name of Old Norse origin, commonly used in Germanic and Scandinavian countries.
  • E. Anastasia Tremaine
    Anastasia Tremaine is one of Cinderella’s stepsisters in Disney’s adaptation, portrayed as a vain and often comically inept antagonist who occasionally shows hints of redemption.
  • 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_69ab49dcee188190b5c6eca9ae9e3469 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abde12b33481908b276760a922db9c completed March 7, 2026, 8:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69afc671964c81908cff1cfbd70c3786 completed March 10, 2026, 7:21 a.m.
Created at: March 6, 2026, 9:59 p.m.