Triple
T20329921
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Norichika Aoki |
E492448
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Aoki |
—
|
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: Aoki | Statement: [Norichika Aoki, familyName, Aoki]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aoki Context triple: [Norichika Aoki, familyName, Aoki]
-
A.
Aoki
chosen
Aoki is a Japanese surname borne by various notable figures in entertainment, sports, and business.
-
B.
Ozaki
Ozaki is a Japanese surname borne by various notable figures in politics, literature, and the arts.
-
C.
Fukuhara
Fukuhara was a historical port district in present-day Kobe, Japan, that briefly served as the seat of the imperial court and political center during the late Heian period.
-
D.
Takeaki
Takeaki is a Japanese given name most notably borne by Enomoto Takeaki, a 19th-century samurai, admiral, and statesman.
-
E.
Akinobu
Akinobu is a Japanese masculine given name that can be written with various kanji combinations and is borne by several notable individuals.
- 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_69e0b4a1a09881908d97270d6971a25a |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e677e6f5d08190bedf376bbb999ebc |
completed | April 20, 2026, 7 p.m. |
Created at: April 16, 2026, 11:22 a.m.