Triple

T9319501
Position Surface form Disambiguated ID Type / Status
Subject Kumamoto Prefecture E224208 entity
Predicate hasMascot P52 FINISHED
Object Kumamon E628600 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: Kumamon | Statement: [Kumamoto Prefecture, hasMascot, Kumamon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kumamon
Context triple: [Kumamoto Prefecture, hasMascot, Kumamon]
  • A. Kumamon chosen
    Kumamon is a popular black bear mascot character created to promote Japan’s Kumamoto Prefecture, known nationwide for its cute, humorous appearance and extensive merchandising.
  • B. Kuromi
    Kuromi is a mischievous yet cute Sanrio character, often depicted in a black jester’s hat with a pink skull, who serves as My Melody’s punk-styled rival.
  • C. Okame
    Okame was a historical figure known primarily as the child of the famed Japanese tea master Sen no Rikyū.
  • D. Konny
    Konny is a diminutive form of the given name Konrad, commonly used as an affectionate nickname.
  • E. Mar-kun
    Mar-kun is one of the official mascots of the Japanese professional baseball team Chiba Lotte Marines, typically depicted as a cheerful seagull character supporting the club.
  • 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_69ca8426d48481909596360f7791c7dd completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd358c7d348190a10fd8670d7756f5 completed April 1, 2026, 3:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69d0c7c1fc848190bbb3ef6a1ed7a7d2 completed April 4, 2026, 8:11 a.m.
Created at: March 30, 2026, 7:38 p.m.