Triple
T19802337
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Satoshi Furukawa |
E475713
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Satoshi Furukawa |
—
|
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: Satoshi Furukawa | Statement: [Satoshi Furukawa, name, Satoshi Furukawa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Satoshi Furukawa Context triple: [Satoshi Furukawa, name, Satoshi Furukawa]
-
A.
Satoshi Furukawa
chosen
Satoshi Furukawa is a Japanese astronaut and physician who has flown long-duration missions to the International Space Station as part of Japan’s space program.
-
B.
Satoshi Mizutani
Satoshi Mizutani is a Japanese virologist known for his pioneering work on retroviruses and reverse transcriptase alongside David Baltimore.
-
C.
Satoshi Nakajima
Satoshi Nakajima is a Japanese professional baseball manager and former catcher best known for leading the Orix Buffaloes to multiple Pacific League titles and a Japan Series championship.
-
D.
Satoshi Ohno
Satoshi Ohno is a Japanese singer, actor, and leader of the popular boy band Arashi.
-
E.
Satoshi Ishii
Satoshi Ishii is a Japanese judoka and mixed martial artist, best known for winning Olympic gold in judo and later competing in major MMA organizations.
- 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_69d8e51bc4208190a1c57d8c5d1b15e4 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e654257cb4819096fb2aa5d1f7fbb0 |
completed | April 20, 2026, 4:28 p.m. |
Created at: April 10, 2026, 1:49 p.m.