Triple

T11575799
Position Surface form Disambiguated ID Type / Status
Subject Friz Freleng E274500 entity
Predicate createdCharacter P2004 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: [Friz Freleng, createdCharacter, Yosemite Sam]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yosemite Sam
Context triple: [Friz Freleng, createdCharacter, 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. Cliff Hare
    Cliff Hare was an influential Auburn University figure and longtime trustee whose contributions to the school's athletics led to his name being honored on Jordan–Hare Stadium.
  • E. 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.
  • 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_69d6aae5ac3c81908d2b0a3a665665b2 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d89049721081909278adfada668ef9 completed April 10, 2026, 5:53 a.m.
NED1 Entity disambiguation (via context triple) batch_69f62a7133d88190813a1e74ef310993 completed May 2, 2026, 4:46 p.m.
Created at: April 8, 2026, 9:38 p.m.