Triple
T1943722
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daisuke Kato |
E42013
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Daisuke
Daisuke is a common Japanese masculine given name used by various notable figures in entertainment, sports, and other fields.
|
E302421
|
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: Daisuke | Statement: [Daisuke Kato, givenName, Daisuke]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Daisuke Context triple: [Daisuke Kato, givenName, Daisuke]
-
A.
Akinobu
Akinobu is a Japanese masculine given name that can be written with various kanji combinations and is borne by several notable individuals.
-
B.
Shintaro
Shintaro is a Japanese given name commonly used for males and borne by various notable figures in sports, entertainment, and politics.
-
C.
Yasuhiro
Yasuhiro is a Japanese masculine given name borne by various notable figures in politics, sports, and entertainment.
-
D.
Kentarō
Kentarō is a Japanese given name commonly used for males, often associated with traditional or strong-sounding name combinations.
-
E.
Takashi
Takashi is a Japanese given name commonly used for males and borne by numerous notable figures in fields such as arts, sports, and entertainment.
- 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: Daisuke Triple: [Daisuke Kato, givenName, Daisuke]
Generated description
Daisuke is a common Japanese masculine given name used by various notable figures in entertainment, sports, and other fields.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Daisuke Target entity description: Daisuke is a common Japanese masculine given name used by various notable figures in entertainment, sports, and other fields.
-
A.
Akinobu
Akinobu is a Japanese masculine given name that can be written with various kanji combinations and is borne by several notable individuals.
-
B.
Shintaro
Shintaro is a Japanese given name commonly used for males and borne by various notable figures in sports, entertainment, and politics.
-
C.
Yasuhiro
Yasuhiro is a Japanese masculine given name borne by various notable figures in politics, sports, and entertainment.
-
D.
Kentarō
Kentarō is a Japanese given name commonly used for males, often associated with traditional or strong-sounding name combinations.
-
E.
Takashi
Takashi is a Japanese given name commonly used for males and borne by numerous notable figures in fields such as arts, sports, and entertainment.
- 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_69a8870e08fc8190a319cbf2600db15f |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb2fe04688190aa8461ba090c93a0 |
completed | March 7, 2026, 5:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afce7154648190aa55d54ca5e50559 |
completed | March 10, 2026, 7:55 a.m. |
| NEDg | Description generation | batch_69afd22a81dc8190809f94f8e49ddad8 |
completed | March 10, 2026, 8:11 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69afd3b8daec81908c5d507e35ba997e |
completed | March 10, 2026, 8:18 a.m. |
Created at: March 4, 2026, 7:36 p.m.