Triple

T20883163
Position Surface form Disambiguated ID Type / Status
Subject How the Grinch Stole Christmas! E514203 entity
Predicate setting P1957 FINISHED
Object Whoville NE NERFINISHED

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: Whoville | Statement: [How the Grinch Stole Christmas!, setting, Whoville]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Whoville
Context triple: [How the Grinch Stole Christmas!, setting, Whoville]
  • A. Whoville chosen
    Whoville is a whimsical, tiny town inhabited by the Whos in Dr. Seuss’s stories, notably featured in both "Horton Hears a Who!" and "How the Grinch Stole Christmas!"
  • B. Snickersville
    Snickersville was the historic name of the rural village now known as Bluemont in Loudoun County, Virginia.
  • C. Toonerville
    Toonerville is the fictional small-town setting featured in the early 20th-century Mickey McGuire comedy stories and film shorts.
  • D. Snowville
    Snowville is a small rural settlement located within the township of Tehkummah in Ontario, Canada.
  • E. Maxville
    Maxville is a small unincorporated community located in the state of Missouri in the United States.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4f733f081908a401c0b7beb0b9f completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c67b03088190be7cbcde8c59509a completed April 21, 2026, 12:36 a.m.
Created at: April 16, 2026, 12:46 p.m.