Triple
T11152380
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shogun |
E263817
|
entity |
| Predicate | executiveProducer |
P7225
|
FINISHED |
| Object |
Kiyoshi Ibuki
Kiyoshi Ibuki is a film and television producer best known for his executive production work on the historical miniseries "Shogun."
|
E1103908
|
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: Kiyoshi Ibuki | Statement: [Shogun, executiveProducer, Kiyoshi Ibuki]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kiyoshi Ibuki Context triple: [Shogun, executiveProducer, Kiyoshi Ibuki]
-
A.
Kiyoshi Nobori
Kiyoshi Nobori is an entrepreneur best known as the founder of the sports equipment company Molten.
-
B.
Kodama Kyūichi
Kodama Kyūichi was a Japanese politician and bureaucrat who served in several high-ranking government and administrative posts in the early 20th century.
-
C.
Makoto Uchida
Makoto Uchida is a Japanese automotive executive who serves as the chief executive officer of Nissan Motor Co.
-
D.
Makoto Kobayashi
Makoto Kobayashi is a Japanese theoretical physicist renowned for his work on CP violation in the Standard Model, for which he shared the 2008 Nobel Prize in Physics.
-
E.
Kenji Aiba
Kenji Aiba is a Japanese local politician who serves as the mayor of the town of Ōiso in Kanagawa Prefecture.
- 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: Kiyoshi Ibuki Triple: [Shogun, executiveProducer, Kiyoshi Ibuki]
Generated description
Kiyoshi Ibuki is a film and television producer best known for his executive production work on the historical miniseries "Shogun."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kiyoshi Ibuki Target entity description: Kiyoshi Ibuki is a film and television producer best known for his executive production work on the historical miniseries "Shogun."
-
A.
Kiyoshi Nobori
Kiyoshi Nobori is an entrepreneur best known as the founder of the sports equipment company Molten.
-
B.
Kodama Kyūichi
Kodama Kyūichi was a Japanese politician and bureaucrat who served in several high-ranking government and administrative posts in the early 20th century.
-
C.
Makoto Uchida
Makoto Uchida is a Japanese automotive executive who serves as the chief executive officer of Nissan Motor Co.
-
D.
Makoto Kobayashi
Makoto Kobayashi is a Japanese theoretical physicist renowned for his work on CP violation in the Standard Model, for which he shared the 2008 Nobel Prize in Physics.
-
E.
Kenji Aiba
Kenji Aiba is a Japanese local politician who serves as the mayor of the town of Ōiso in Kanagawa Prefecture.
- 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_69d6aa9ccddc8190868998c8b7beb060 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8719e74819095413abc6c79296c |
completed | April 9, 2026, 5:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd7a2796cc81908b6d4cf71f39e88a |
completed | May 8, 2026, 5:52 a.m. |
| NEDg | Description generation | batch_69fd7cb98ba08190bddf0656c44e8d4e |
completed | May 8, 2026, 6:03 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd7d58e5308190a1352d1698ddb58b |
completed | May 8, 2026, 6:06 a.m. |
Created at: April 8, 2026, 9:28 p.m.