Triple
T15629346
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 純一郎 |
E375766
|
entity |
| Predicate | typicalNameOrderInJapanese |
P20511
|
FINISHED |
| Object | family name followed by given name |
—
|
LITERAL 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: family name followed by given name | Statement: [純一郎, typicalNameOrderInJapanese, family name followed by given name]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalNameOrderInJapanese Context triple: [純一郎, typicalNameOrderInJapanese, family name followed by given name]
-
A.
nameOrderInJapan
chosen
Indicates that the person’s name is written or presented in the Japanese order, with the family name appearing before the given name.
-
B.
rankInJapaneseOrders
Indicates the position or level an entity holds within the hierarchy of Japanese orders, decorations, or honors.
-
C.
nameInJapaneseKana
Indicates that an entity’s name is written or represented using Japanese kana characters.
-
D.
hasNameInJapanese
Indicates that an entity is associated with a specific name expressed in the Japanese language.
-
E.
eraNameInJapanese
Indicates the Japanese-language name used for a specific historical or calendar era.
- F. None of above.
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_69d85cd035a48190b73d5579ab73969a |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04eb4301881908c7157227fdf79b6 |
completed | April 16, 2026, 2:51 a.m. |
| PD | Predicate disambiguation | batch_69deda868d4481908f4bce1c64d2902a |
completed | April 15, 2026, 12:23 a.m. |
Created at: April 10, 2026, 4:14 a.m.