Triple

T2082624
Position Surface form Disambiguated ID Type / Status
Subject Frozen Ever After E45276 entity
Predicate featuresCharacter P626 FINISHED
Object Kristoff E173080 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: Kristoff | Statement: [Frozen Ever After, featuresCharacter, Kristoff]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kristoff
Context triple: [Frozen Ever After, featuresCharacter, Kristoff]
  • A. Kristoff chosen
    Kristoff is a rugged, kind-hearted ice harvester and one of the central human protagonists in Disney's animated film "Frozen."
  • B. Olaf
    Olaf is a masculine given name of Old Norse origin, commonly used in Germanic and Scandinavian countries.
  • C. Nils
    Nils is a Scandinavian male given name, commonly used in countries like Norway and Sweden and derived from the name Nicholas.
  • D. Ice King
    Ice King is the nickname of Frederick Tudor, a 19th-century American entrepreneur who pioneered the international ice trade by shipping harvested ice worldwide.
  • 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_69a8891869c88190a02643e3bb746f59 completed March 4, 2026, 7:33 p.m.
NER Named-entity recognition batch_69abba5097ac8190a723a8af2982238c completed March 7, 2026, 5:40 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae3058a7b48190879edde4d97ca102 completed March 9, 2026, 2:28 a.m.
Created at: March 4, 2026, 7:41 p.m.