Triple

T20573780
Position Surface form Disambiguated ID Type / Status
Subject MultiVersus E505161 entity
Predicate includesCharacter P5716 FINISHED
Object Jake the Dog 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: Jake the Dog | Statement: [MultiVersus, includesCharacter, Jake the Dog]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jake the Dog
Context triple: [MultiVersus, includesCharacter, Jake the Dog]
  • A. Jake the Dog chosen
    Jake the Dog is a magical, shape-shifting dog and one of the two main protagonists of the animated television series Adventure Time.
  • B. Beasley the Dog
    Beasley the Dog was the canine actor best known for playing the slobbery Dogue de Bordeaux partner to Tom Hanks in the 1989 film "Turner & Hooch."
  • C. Piper the Dog
    Piper the Dog is the costumed canine mascot representing Hamline University at its athletic events and campus activities.
  • D. Jack the dog
    Jack the dog is a fictional canine character appearing in the animated television series "The Artist."
  • E. Jake the Peg
    "Jake the Peg" is a novelty song and comedic performance piece, popularized by entertainer Rolf Harris, about a man humorously claiming to have an extra leg.
  • 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_69e0b4b721588190993ac7b0a9be2736 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6a9087af88190a4610ecb29f637ca completed April 20, 2026, 10:30 p.m.
Created at: April 16, 2026, 11:39 a.m.