Triple
T19448263
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kawamura Sumiyoshi |
E486542
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Kawamura |
—
|
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: Kawamura | Statement: [Kawamura Sumiyoshi, familyName, Kawamura]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kawamura Context triple: [Kawamura Sumiyoshi, familyName, Kawamura]
-
A.
Kawamura Sumiyoshi
chosen
Kawamura Sumiyoshi was a Meiji-era Japanese general best known for leading imperial government forces that defeated Saigō Takamori in the Satsuma Rebellion.
-
B.
Makoto Kano
Makoto Kano is a Japanese video game designer best known for his influential work at Nintendo on classic franchises such as Metroid and Kid Icarus.
-
C.
Akinobu
Akinobu is a Japanese masculine given name that can be written with various kanji combinations and is borne by several notable individuals.
-
D.
Okamura Daiki
Okamura Daiki is a Japanese individual notable enough to be specifically distinguished from others sharing the surname Okamura.
-
E.
Tanaka Koki
Tanaka Koki is a Japanese entertainer best known as a former member of the popular boy band KAT-TUN.
- 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_69d8e8d7ad488190a3373045029b0f3b |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6338be5a48190973d9ecae853900c |
completed | April 20, 2026, 2:09 p.m. |
Created at: April 10, 2026, 1:38 p.m.