Triple

T3302668
Position Surface form Disambiguated ID Type / Status
Subject Wisconsin Badgers football E69370 entity
Predicate mascot P52 FINISHED
Object Bucky Badger E75596 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: Bucky Badger | Statement: [Wisconsin Badgers football, mascot, Bucky Badger]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bucky Badger
Context triple: [Wisconsin Badgers football, mascot, Bucky Badger]
  • A. Bucky Badger chosen
    Bucky Badger is the cartoon badger mascot of the University of Wisconsin–Madison, known for representing the school's athletic teams and spirit at sporting events and campus activities.
  • B. Banzi
    Banzi is a town in the Basilicata region of southern Italy, known as the modern site near the ancient Lucanian city of Bantia.
  • C. Bucky
    Bucky is a wiry, fast-talking member of the Junkyard Gang in the animated series "Fat Albert and the Cosby Kids," known for his distinctive buck teeth and energetic personality.
  • D. Badger
    Badger is a fictional character appearing in the work "The Return of Ulysses."
  • E. Badger
    Badger is a wise, kind, and somewhat reclusive character from Kenneth Grahame’s "The Wind in the Willows," known for offering guidance and shelter to his woodland friends.
  • 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_69ad859e529c8190a404273f53cb487d completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb0a9450481909f0d630e5593085e completed March 8, 2026, 5:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69b2f3df7f548190ada47f742df46545 completed March 12, 2026, 5:11 p.m.
Created at: March 8, 2026, 3:11 p.m.