Triple
T17470254
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Masaru Ibuka |
E425390
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Masaru |
—
|
NE NERFINISHED |
How this triple was built (2 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.
Masaru
chosen
Masaru is a Japanese given name commonly used for males and borne by various notable figures in fields such as technology, sports, and entertainment.
-
B.
Matsuwakamaro
Matsuwakamaro is the childhood name of Shinran, the influential Japanese Buddhist monk who founded Jōdo Shinshū (True Pure Land) Buddhism.
-
C.
Gosamaru
Gosamaru was a prominent 15th-century Ryukyuan lord and military commander known for constructing key gusuku (castle) fortresses and playing a central role in the political unification of the Ryukyu Kingdom.
-
D.
Masayuki
Masayuki is a Japanese given name commonly used for males.
-
E.
Tajōmaru
Tajōmaru is the notorious bandit whose conflicting testimonies drive the plot and themes of truth and perception in Ryūnosuke Akutagawa’s short story "In a Grove."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d889dbc2e88190b18ea6115e819258 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e451aad4a08190be7e25841da8e952 |
completed | April 19, 2026, 3:53 a.m. |
Created at: April 10, 2026, 5:47 a.m.