Triple
T2333065
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Masataka Yoshida |
E44246
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Yoshida |
E205404
|
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: Yoshida | Statement: [Masataka Yoshida, familyName, Yoshida]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yoshida Context triple: [Masataka Yoshida, familyName, Yoshida]
-
A.
Yoshida
chosen
Yoshida is a common Japanese surname borne by numerous notable figures in politics, arts, sports, and entertainment.
-
B.
Yasuji
Yasuji is a Japanese given name commonly used for males and borne by various notable figures in Japan.
-
C.
Murayama
Murayama is a Japanese surname borne by various notable individuals across fields such as politics, science, and the arts.
-
D.
Takaishi
Takaishi is a city in Osaka Prefecture, Japan, known as a small industrial and residential hub within the Osaka metropolitan area.
-
E.
Wakatsuki
Wakatsuki was a Japanese destroyer of the Imperial Japanese Navy that served in World War II before being sunk during late-war Pacific naval operations.
- 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_69a889132b488190bbb43ad4780ddd92 |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abc66d7ea081908867ff494b70df1e |
completed | March 7, 2026, 6:32 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b3544c5fcc8190b2d8d61449dfffb3 |
completed | March 13, 2026, 12:03 a.m. |
Created at: March 4, 2026, 7:51 p.m.