Triple

T7483764
Position Surface form Disambiguated ID Type / Status
Subject DuckTales (2017) E176827 entity
Predicate setting P1957 FINISHED
Object Duckburg E173096 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: Duckburg | Statement: [DuckTales (2017), setting, Duckburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Duckburg
Context triple: [DuckTales (2017), setting, Duckburg]
  • A. Duckburg chosen
    Duckburg is a fictional American city in Disney comics and cartoons, best known as the hometown of Donald Duck, Scrooge McDuck, and many other characters from the Mickey Mouse universe.
  • B. Toonerville
    Toonerville is the fictional small-town setting featured in the early 20th-century Mickey McGuire comedy stories and film shorts.
  • C. Windmill City
    Windmill City is a nickname for Batavia, Illinois, reflecting its historic association with windmill manufacturing and numerous preserved windmills.
  • D. Thneedville
    Thneedville is the brightly colored, artificial city in the 2012 animated film "The Lorax," where residents live surrounded by plastic and metal with no real trees or nature.
  • E. Blissville
    Blissville is a small, historically industrial neighborhood in western Queens, New York City, known for its proximity to major rail yards and cemeteries.
  • 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_69c69f24ac508190bb98fe927c0bd065 completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f53923e4819081bf79ed962a971c completed March 27, 2026, 9:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8349d83cc8190af98c3212e28e913 completed March 28, 2026, 8:05 p.m.
Created at: March 27, 2026, 3:42 p.m.