Triple

T17313511
Position Surface form Disambiguated ID Type / Status
Subject Ono E420360 entity
Predicate hasNotableBearer P458 FINISHED
Object Yuta Ono
Yuta Ono is a Japanese individual notable enough to be recognized as a bearer of the surname Ono, likely in a professional or public context such as sports, arts, or entertainment.
 E1266288 NE FINISHED

How this triple was built (4 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: Yuta Ono | Statement: [Ono, hasNotableBearer, Yuta Ono]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Yuta Ono
Context triple: [Ono, hasNotableBearer, Yuta Ono]
  • A. Yuta Nakamura
    Yuta Nakamura is a Japanese individual notable enough to be recognized as a prominent bearer of the Nakamura surname.
  • B. Yuta Watase
    Yuta Watase is a Japanese ski jumper who has competed internationally as a member of Japan’s national team.
  • C. Yuta Tabuse
    Yuta Tabuse is a Japanese professional basketball point guard best known as the first Japanese-born player to appear in an NBA regular-season game.
  • D. Yuto Nakamura
    Yuto Nakamura is a Japanese given name bearer, likely known as a public figure such as an athlete, entertainer, or professional in Japan.
  • E. Mirai Yamamoto
    Mirai Yamamoto is a Japanese actress known for her roles in film and television since the late 1990s.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Yuta Ono
Triple: [Ono, hasNotableBearer, Yuta Ono]
Generated description
Yuta Ono is a Japanese individual notable enough to be recognized as a bearer of the surname Ono, likely in a professional or public context such as sports, arts, or entertainment.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Yuta Ono
Target entity description: Yuta Ono is a Japanese individual notable enough to be recognized as a bearer of the surname Ono, likely in a professional or public context such as sports, arts, or entertainment.
  • A. Yuta Nakamura
    Yuta Nakamura is a Japanese individual notable enough to be recognized as a prominent bearer of the Nakamura surname.
  • B. Yuta Watase
    Yuta Watase is a Japanese ski jumper who has competed internationally as a member of Japan’s national team.
  • C. Yuta Tabuse
    Yuta Tabuse is a Japanese professional basketball point guard best known as the first Japanese-born player to appear in an NBA regular-season game.
  • D. Yuto Nakamura
    Yuto Nakamura is a Japanese given name bearer, likely known as a public figure such as an athlete, entertainer, or professional in Japan.
  • E. Mirai Yamamoto
    Mirai Yamamoto is a Japanese actress known for her roles in film and television since the late 1990s.
  • F. None of above. chosen

Provenance (5 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_69d889d22b848190a4663d0b8f8f76e7 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e4399a4194819091d34cd3fffc8072 completed April 19, 2026, 2:10 a.m.
NED1 Entity disambiguation (via context triple) batch_6a019fe3631481909c7df5ba95a1bfc0 completed May 11, 2026, 9:22 a.m.
NEDg Description generation batch_6a01a130756c8190a8f213141e63d792 completed May 11, 2026, 9:28 a.m.
NED2 Entity disambiguation (via description) batch_6a01a1c415dc8190ba8f7e2a8053917f completed May 11, 2026, 9:30 a.m.
Created at: April 10, 2026, 5:43 a.m.