Triple

T1770385
Position Surface form Disambiguated ID Type / Status
Subject Sukki E38860 entity
Predicate partOf P40 FINISHED
Object Snowlets E38345 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: Snowlets | Statement: [Sukki, partOf, Snowlets]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Snowlets
Context triple: [Sukki, partOf, Snowlets]
  • A. Snowlets chosen
    Snowlets are the four snowy owl mascots created to represent the 1998 Winter Olympics in Nagano, Japan.
  • B. Snowbird
    Snowbird is a major ski and snowboard resort in Utah known for its steep terrain, deep powder, and long winter season.
  • C. Snowman
    Snowman is the post-apocalyptic survivor and narrator of Margaret Atwood’s dystopian novel "Oryx and Crake," through whose perspective the story’s ruined world and its origins are revealed.
  • D. Fuwa
    Fuwa are the five official mascots of the 2008 Beijing Olympic Games, each representing a different color of the Olympic rings and elements of Chinese culture and symbolism.
  • E. Alupka
    Alupka is a resort town on the southern coast of Crimea, known for the Neo-Gothic and Moorish-style Vorontsov Palace and its scenic location at the foot of Mount Ai-Petri.
  • 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_69a8862e61708190af97b9838cc3f5de completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa648eb9488190b1be2d2b6d259634 completed March 6, 2026, 5:22 a.m.
NED1 Entity disambiguation (via context triple) batch_69adbf4fd0ec8190904f1ad2155c58bf completed March 8, 2026, 6:26 p.m.
Created at: March 4, 2026, 7:31 p.m.