Triple

T3108144
Position Surface form Disambiguated ID Type / Status
Subject Melvin Jerome Blanc E64883 entity
Predicate voicedCharacter P2000 FINISHED
Object Yosemite Sam E57131 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: Yosemite Sam | Statement: [Melvin Jerome Blanc, voicedCharacter, Yosemite Sam]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yosemite Sam
Context triple: [Melvin Jerome Blanc, voicedCharacter, Yosemite Sam]
  • A. Yosemite Sam chosen
    Yosemite Sam is a hot-tempered, mustachioed outlaw and recurring antagonist in the Looney Tunes cartoons, known for his fiery personality and frequent clashes with Bugs Bunny.
  • B. Elmer Fudd
    Elmer Fudd is a classic Looney Tunes cartoon character best known as the bumbling, soft-spoken hunter perpetually chasing Bugs Bunny.
  • C. Charlie Coyote
    Charlie Coyote is the costumed athletic mascot representing the University of South Dakota’s sports teams.
  • D. Wile E. Coyote
    Wile E. Coyote is a classic Looney Tunes cartoon character best known as the endlessly scheming, perpetually failing predator obsessed with catching the Road Runner.
  • E. Laffing Sal
    Laffing Sal is a historic, animatronic laughing woman figure from early 20th-century amusement parks, now preserved as a popular attraction at San Francisco’s Musée Mécanique.
  • 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_69ad857eeaf48190b34ebfdaa7a264cf completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada29eacc88190a19c5ca8e53e3dca completed March 8, 2026, 4:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69b2038c89248190b880108c82ad35b1 completed March 12, 2026, 12:06 a.m.
Created at: March 8, 2026, 3:04 p.m.