Triple

T2532570
Position Surface form Disambiguated ID Type / Status
Subject Vanessa Kirby E56194 entity
Predicate familyName P18 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: [Vanessa Kirby, familyName, Kirby]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kirby
Context triple: [Vanessa Kirby, familyName, 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. 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.
  • C. 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.
  • D. Mario & Luigi
    Mario & Luigi is a role-playing video game series by Nintendo that follows the comedic, cooperative adventures of Mario and his brother Luigi.
  • E. Mario
    Mario is an American R&B singer, songwriter, and occasional actor best known for his early-2000s hits like "Let Me Love You."
  • 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_69ab4a49b6508190bc467fbef4bac334 completed March 6, 2026, 9:42 p.m.
NER Named-entity recognition batch_69abd279cf108190b03fb6e0265f39d9 completed March 7, 2026, 7:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69af2bb9c37081909128d7a227651c8b completed March 9, 2026, 8:21 p.m.
Created at: March 6, 2026, 9:47 p.m.