Triple
T2511682
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Masaru Ibuka |
E52715
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Masaru
Masaru is a Japanese given name commonly used for males and borne by various notable figures in fields such as technology, sports, and entertainment.
|
E332320
|
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: Masaru | Statement: [Masaru Ibuka, givenName, Masaru]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Masaru Context triple: [Masaru Ibuka, givenName, Masaru]
-
A.
Masayuki
Masayuki is a Japanese given name commonly used for males.
-
B.
Kenjirō
Kenjirō is a Japanese masculine given name that can be written with various kanji combinations and is borne by multiple notable individuals in fields such as sports, arts, and entertainment.
-
C.
Kintomo Mushakoji
Kintomo Mushakoji was a Japanese diplomat who served as a key representative of Japan’s government in the 1930s, notably involved in its alignment with Axis powers.
-
D.
Masaharu
Masaharu is a Japanese masculine given name that can be written with various kanji combinations and is borne by several notable figures in Japanese history and culture.
-
E.
Shinpei
Shinpei is a Japanese given name commonly used for males and borne by various notable figures in politics, arts, 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: Masaru Triple: [Masaru Ibuka, givenName, Masaru]
Generated description
Masaru is a Japanese given name commonly used for males and borne by various notable figures in fields such as technology, sports, and entertainment.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Masaru Target entity description: Masaru is a Japanese given name commonly used for males and borne by various notable figures in fields such as technology, sports, and entertainment.
-
A.
Masayuki
Masayuki is a Japanese given name commonly used for males.
-
B.
Kenjirō
Kenjirō is a Japanese masculine given name that can be written with various kanji combinations and is borne by multiple notable individuals in fields such as sports, arts, and entertainment.
-
C.
Kintomo Mushakoji
Kintomo Mushakoji was a Japanese diplomat who served as a key representative of Japan’s government in the 1930s, notably involved in its alignment with Axis powers.
-
D.
Masaharu
Masaharu is a Japanese masculine given name that can be written with various kanji combinations and is borne by several notable figures in Japanese history and culture.
-
E.
Shinpei
Shinpei is a Japanese given name commonly used for males and borne by various notable figures in politics, arts, 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_69ab4958e76481908a235377dd921c9e |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abd1efb5c48190a9b47b39a388412b |
completed | March 7, 2026, 7:21 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b2248bcb68819095e52fea4cd5692c |
completed | March 12, 2026, 2:27 a.m. |
| NEDg | Description generation | batch_69b228768ee4819094da89f907e48deb |
completed | March 12, 2026, 2:44 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b22903b428819083af822577861a6b |
completed | March 12, 2026, 2:46 a.m. |
Created at: March 6, 2026, 9:46 p.m.