Triple
T2160469
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Isuzu |
E47989
|
entity |
| Predicate | foundedBy |
P104
|
FINISHED |
| Object | Yoshisuke Aikawa |
E248417
|
NE FINISHED |
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: Yoshisuke Aikawa | Statement: [Isuzu, foundedBy, Yoshisuke Aikawa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yoshisuke Aikawa Context triple: [Isuzu, foundedBy, Yoshisuke Aikawa]
-
A.
Yoshisuke Aikawa
chosen
Yoshisuke Aikawa was a prominent Japanese industrialist and entrepreneur best known as the founding leader who built Nissan into a major automotive and industrial conglomerate.
-
B.
Tatsuhiko Kawashima
Tatsuhiko Kawashima is a Japanese academic and former professor best known as the father of Princess Kiko of the Japanese Imperial Family.
-
C.
Shigeru Fukudome
Shigeru Fukudome was a senior admiral in the Imperial Japanese Navy who held key staff and command positions during World War II.
-
D.
Yūsaku Kamekura
Yūsaku Kamekura was a pioneering Japanese graphic designer renowned for his modernist posters and visual identities, including iconic work for the 1964 Tokyo Olympics.
-
E.
Takeo Kanade
Takeo Kanade is a pioneering Japanese computer scientist and roboticist renowned for his foundational contributions to computer vision, robotics, and autonomous systems.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69a88a1d1fd8819088b34990d69a712f |
completed | March 4, 2026, 7:38 p.m. |
| NER | Named-entity recognition | batch_69abbe8894d481908eda9363fd36fea6 |
completed | March 7, 2026, 5:58 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b65047902881908a1d5f2d32fcb23e |
completed | March 15, 2026, 6:23 a.m. |
Created at: March 4, 2026, 7:45 p.m.