Triple
T6274771
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kikuchi |
E140627
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Yoshihiro Kikuchi
Yoshihiro Kikuchi is a Japanese individual notable enough to be recognized as a distinct namesake of the surname Kikuchi.
|
E935439
|
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: Yoshihiro Kikuchi | Statement: [Kikuchi, hasNotableBearer, Yoshihiro Kikuchi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yoshihiro Kikuchi Context triple: [Kikuchi, hasNotableBearer, Yoshihiro Kikuchi]
-
A.
Katsuya Okada
Katsuya Okada is a Japanese politician who has served as leader of the Democratic Party of Japan and as Deputy Prime Minister.
-
B.
Naoki Yoshimura
Naoki Yoshimura is a Japanese politician who served as the governor of Osaka Prefecture and is known for his role in regional administrative reform efforts.
-
C.
Masahiro Hirakubo
Masahiro Hirakubo is a Japanese film editor best known for his work on acclaimed films such as "Trainspotting" and "The Beach."
-
D.
Tatsuhiko Kawashima
Tatsuhiko Kawashima is a Japanese academic and former professor best known as the father of Princess Kiko of the Japanese Imperial Family.
-
E.
Koichi Tanaka
Koichi Tanaka is a Japanese engineer and Nobel Prize–winning chemist renowned for his pioneering work in mass spectrometry, particularly soft laser desorption ionization.
- 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: Yoshihiro Kikuchi Triple: [Kikuchi, hasNotableBearer, Yoshihiro Kikuchi]
Generated description
Yoshihiro Kikuchi is a Japanese individual notable enough to be recognized as a distinct namesake of the surname Kikuchi.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Yoshihiro Kikuchi Target entity description: Yoshihiro Kikuchi is a Japanese individual notable enough to be recognized as a distinct namesake of the surname Kikuchi.
-
A.
Katsuya Okada
Katsuya Okada is a Japanese politician who has served as leader of the Democratic Party of Japan and as Deputy Prime Minister.
-
B.
Naoki Yoshimura
Naoki Yoshimura is a Japanese politician who served as the governor of Osaka Prefecture and is known for his role in regional administrative reform efforts.
-
C.
Masahiro Hirakubo
Masahiro Hirakubo is a Japanese film editor best known for his work on acclaimed films such as "Trainspotting" and "The Beach."
-
D.
Tatsuhiko Kawashima
Tatsuhiko Kawashima is a Japanese academic and former professor best known as the father of Princess Kiko of the Japanese Imperial Family.
-
E.
Koichi Tanaka
Koichi Tanaka is a Japanese engineer and Nobel Prize–winning chemist renowned for his pioneering work in mass spectrometry, particularly soft laser desorption ionization.
- 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_69c008cc158881908df6ec94a911c736 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c063c0629c8190805ddf1a604e9ca4 |
completed | March 22, 2026, 9:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e712b2ff1081908ccf311e1133ab72 |
completed | April 21, 2026, 6:01 a.m. |
| NEDg | Description generation | batch_69e720f4015c81909ba7973c3e781985 |
completed | April 21, 2026, 7:02 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69e75a7a04c88190bb8f3dd3f3e435ef |
completed | April 21, 2026, 11:07 a.m. |
Created at: March 22, 2026, 4:25 p.m.