Triple

T7644180
Position Surface form Disambiguated ID Type / Status
Subject Kingdom of Arendelle E173079 entity
Predicate hasResident P6481 FINISHED
Object Olaf E57859 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: Olaf | Statement: [Kingdom of Arendelle, hasResident, Olaf]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Olaf
Context triple: [Kingdom of Arendelle, hasResident, Olaf]
  • A. Olaf chosen
    Olaf is a masculine given name of Old Norse origin, commonly used in Germanic and Scandinavian countries.
  • B. Olaf Haraldsson
    Olaf Haraldsson, also known as Saint Olaf, was an 11th-century king of Norway whose efforts to consolidate Christianity and royal power made him a central figure in Norwegian history and later its patron saint.
  • C. Nils
    Nils is a Scandinavian male given name, commonly used in countries like Norway and Sweden and derived from the name Nicholas.
  • D. Kristoff
    Kristoff is a rugged, kind-hearted ice harvester and one of the central human protagonists in Disney's animated film "Frozen."
  • E. Finn
    Finn is a central character in the Star Wars sequel trilogy, a former stormtrooper who defects from the First Order and joins the Resistance.
  • 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_69c6995360188190968ee57b72a1627f completed March 27, 2026, 2:50 p.m.
NER Named-entity recognition batch_69c6faf13858819095262664e1e04eb7 completed March 27, 2026, 9:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69c89acaac6481908ef763647a0ca9b3 completed March 29, 2026, 3:21 a.m.
Created at: March 27, 2026, 3:58 p.m.