Triple

T6911488
Position Surface form Disambiguated ID Type / Status
Subject Frosty Day Parade E159942 entity
Predicate featuresCharacter P626 FINISHED
Object Frosty the Snowman E627751 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: Frosty the Snowman | Statement: [Frosty Day Parade, featuresCharacter, Frosty the Snowman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Frosty the Snowman
Context triple: [Frosty Day Parade, featuresCharacter, Frosty the Snowman]
  • A. Frosty the Snowman chosen
    Frosty the Snowman is a popular Christmas character and song figure, depicted as a magically animated snowman who comes to life and has joyful winter adventures.
  • B. Rudolph
    Rudolph is the legendary red-nosed reindeer from Christmas folklore who guides Santa Claus’s sleigh through the night.
  • C. Rudolph
    Rudolph is a surname of German origin borne by various notable individuals and families.
  • D. Rudolph
    Rudolph is the full given name of Rudy Giuliani, the former mayor of New York City and prominent American political figure.
  • E. 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.
  • 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_69c68839ccb88190b4aa5cc1aca3448f completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6d9c135b48190b332aedf1d52bdb7 completed March 27, 2026, 7:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69c75127b71c8190ac958a178795dcf7 completed March 28, 2026, 3:55 a.m.
Created at: March 27, 2026, 2:25 p.m.