Triple
T17313507
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ono |
E420360
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Koji Ono
Koji Ono is a Japanese individual notable enough to be specifically distinguished from others sharing the surname Ono, though detailed public information about his achievements is limited.
|
E1263032
|
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: Koji Ono | Statement: [Ono, hasNotableBearer, Koji Ono]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Koji Ono Context triple: [Ono, hasNotableBearer, Koji Ono]
-
A.
Mika Ono
Mika Ono is a Japanese individual known for bearing the surname Ono, though specific widely recognized public achievements or roles are not well documented.
-
B.
Yukihiro Ohno
Yukihiro Ohno is a Japanese individual notable enough to be specifically cited as a bearer of the surname Ohno.
-
C.
Ono
Ono is a Japanese surname borne by various notable individuals across fields such as academia, politics, and the arts.
-
D.
Ono
Ono is a keen-eyed egret from Disney Junior’s animated series “The Lion Guard,” serving as the team’s observant and intelligent lookout.
-
E.
Hitoshi Ono
Hitoshi Ono is a Japanese mathematician known for his contributions to numerical analysis and finite element methods.
- 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: Koji Ono Triple: [Ono, hasNotableBearer, Koji Ono]
Generated description
Koji Ono is a Japanese individual notable enough to be specifically distinguished from others sharing the surname Ono, though detailed public information about his achievements is limited.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Koji Ono Target entity description: Koji Ono is a Japanese individual notable enough to be specifically distinguished from others sharing the surname Ono, though detailed public information about his achievements is limited.
-
A.
Mika Ono
Mika Ono is a Japanese individual known for bearing the surname Ono, though specific widely recognized public achievements or roles are not well documented.
-
B.
Yukihiro Ohno
Yukihiro Ohno is a Japanese individual notable enough to be specifically cited as a bearer of the surname Ohno.
-
C.
Ono
Ono is a Japanese surname borne by various notable individuals across fields such as academia, politics, and the arts.
-
D.
Ono
Ono is a keen-eyed egret from Disney Junior’s animated series “The Lion Guard,” serving as the team’s observant and intelligent lookout.
-
E.
Hitoshi Ono
Hitoshi Ono is a Japanese mathematician known for his contributions to numerical analysis and finite element methods.
- 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_6a018c4603f88190a713bf8260329ac3 |
completed | May 11, 2026, 7:59 a.m. |
| NEDg | Description generation | batch_6a018d40df188190b8cd943ac8adf6fc |
completed | May 11, 2026, 8:03 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a018f5c90f88190b36b512defc43bac |
completed | May 11, 2026, 8:12 a.m. |
Created at: April 10, 2026, 5:43 a.m.