Triple
T15115203
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tomoyuki Yamashita |
E361017
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Tomoyuki |
E315805
|
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: Tomoyuki | Statement: [Tomoyuki Yamashita, givenName, Tomoyuki]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tomoyuki Context triple: [Tomoyuki Yamashita, givenName, Tomoyuki]
-
A.
Tomoyuki
chosen
Tomoyuki is a Japanese masculine given name borne by various notable figures in fields such as the military, arts, and entertainment.
-
B.
Tomoyasu
Tomoyasu is a Japanese masculine given name borne by various notable individuals, including musicians and athletes.
-
C.
Tomonori
Tomonori is a Japanese masculine given name used by various notable individuals in fields such as sports and entertainment.
-
D.
Takahito
Takahito, better known by his title Prince Mikasa, was a member of the Japanese imperial family and the youngest son of Emperor Taishō.
-
E.
Taisuke
Taisuke is a Japanese given name notably borne by historical figures such as the Meiji-era politician Itagaki Taisuke.
- 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_69d85a0491ec8190830960be8fafb994 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0058f4fb88190a3d446a466aebcf1 |
completed | April 15, 2026, 9:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a002d92c9788190aa4523a1e47bc561 |
completed | May 10, 2026, 7:02 a.m. |
Created at: April 10, 2026, 3:05 a.m.