Triple

T5080186
Position Surface form Disambiguated ID Type / Status
Subject Kirby E114492 entity
Predicate franchise P1500 FINISHED
Object Kirby E114492 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: Kirby | Statement: [Kirby, franchise, Kirby]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kirby
Context triple: [Kirby, franchise, Kirby]
  • A. Kirby chosen
    Kirby is a popular Nintendo video game character and series starring a small pink, shape-shifting hero who inhales enemies to copy their abilities.
  • B. Kirby Krackle
    Kirby Krackle is a distinctive comic book art technique characterized by clusters of black dots used to depict cosmic energy, explosions, and other powerful forces, most famously associated with artist Jack Kirby.
  • C. City of Kirby
    The City of Kirby is a small suburban municipality located within the San Antonio metropolitan area in Bexar County, Texas.
  • D. Taitō
    Taitō is a special ward in central Tokyo known for its historic districts, traditional temples, and major cultural attractions such as Ueno Park and Asakusa.
  • E. Yoshi
    Yoshi is a friendly, dinosaur-like character from Nintendo’s Mario franchise, known for his long tongue, egg-throwing abilities, and frequent role as Mario’s companion and steed.
  • 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_69bd443dbf908190a9401e9c2dc7bd7d completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd74f86c988190aa026073ed435a45 completed March 20, 2026, 4:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69beb1303bc4819084e0270a8ff97aec completed March 21, 2026, 2:54 p.m.
Created at: March 20, 2026, 1:39 p.m.