Triple
T14087954
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ryogo Kubo |
E339046
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Ryogo
Ryogo is a Japanese given name most notably borne by theoretical physicist Ryogo Kubo, known for his contributions to statistical mechanics and the fluctuation-dissipation theorem.
|
E1149308
|
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: Ryogo | Statement: [Ryogo Kubo, givenName, Ryogo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ryogo Context triple: [Ryogo Kubo, givenName, Ryogo]
-
A.
Ryojun
Ryojun is the former Japanese name for Lüshunkou, a strategically important port city in northeastern China historically known for its military significance.
-
B.
Ryūō
Ryūō is a town in Shiga Prefecture, Japan, known for its location near Lake Biwa and its blend of rural landscapes with growing commercial development.
-
C.
Yorii
Yorii is a town in Saitama Prefecture, Japan, known as a regional residential and commuter hub connected to the greater Tokyo area.
-
D.
Yorihito
Yorihito was a Japanese imperial prince of the Higashifushimi-no-miya house who served as a high-ranking naval officer during the late Meiji and Taishō periods.
-
E.
Kinsaku
Kinsaku is the birth name of Matsuo Bashō, the renowned 17th-century Japanese haiku poet and literary figure.
- 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: Ryogo Triple: [Ryogo Kubo, givenName, Ryogo]
Generated description
Ryogo is a Japanese given name most notably borne by theoretical physicist Ryogo Kubo, known for his contributions to statistical mechanics and the fluctuation-dissipation theorem.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ryogo Target entity description: Ryogo is a Japanese given name most notably borne by theoretical physicist Ryogo Kubo, known for his contributions to statistical mechanics and the fluctuation-dissipation theorem.
-
A.
Ryojun
Ryojun is the former Japanese name for Lüshunkou, a strategically important port city in northeastern China historically known for its military significance.
-
B.
Ryūō
Ryūō is a town in Shiga Prefecture, Japan, known for its location near Lake Biwa and its blend of rural landscapes with growing commercial development.
-
C.
Yorii
Yorii is a town in Saitama Prefecture, Japan, known as a regional residential and commuter hub connected to the greater Tokyo area.
-
D.
Yorihito
Yorihito was a Japanese imperial prince of the Higashifushimi-no-miya house who served as a high-ranking naval officer during the late Meiji and Taishō periods.
-
E.
Kinsaku
Kinsaku is the birth name of Matsuo Bashō, the renowned 17th-century Japanese haiku poet and literary figure.
- 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_69d81c687b0c819087fd9ed4198403f8 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de5ee1ce88819091c983286289337e |
completed | April 14, 2026, 3:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fef883f2b88190807d9157e8d45e3c |
completed | May 9, 2026, 9:04 a.m. |
| NEDg | Description generation | batch_69fef9b42b94819088e96f301a91ce71 |
completed | May 9, 2026, 9:09 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fefa179c7081908cced4ad780583a3 |
completed | May 9, 2026, 9:10 a.m. |
Created at: April 9, 2026, 10:21 p.m.