Triple
T16424742
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Naoko Satō |
E398912
|
entity |
| Predicate | hasSurnameFrequency |
P122732
|
FINISHED |
| Object | Satō is one of the most common surnames in Japan |
—
|
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: Satō is one of the most common surnames in Japan | Statement: [Naoko Satō, hasSurnameFrequency, Satō is one of the most common surnames in Japan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSurnameFrequency Context triple: [Naoko Satō, hasSurnameFrequency, Satō is one of the most common surnames in Japan]
-
A.
hasBaseSurname
Indicates that an entity’s surname is derived from, or fundamentally corresponds to, a specified base or canonical surname.
-
B.
hasSurnameType
Indicates that an entity’s surname belongs to a particular category or type (e.g., patronymic, toponymic, occupational).
-
C.
hasSurnamePattern
Indicates that an entity’s surname follows or matches a specified structural or stylistic pattern.
-
D.
isSurname
Indicates that one entity is the family name (last name) of another entity.
-
E.
hasSeptSurname
Indicates that an entity bears a surname associated with a particular sept (a family subgroup or clan division).
- F. None of above. chosen
Provenance (4 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_69d87f2b9024819085c20e52de95d583 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e328f9da9081908dadbdac4b2d38ec |
completed | April 18, 2026, 6:47 a.m. |
| PD | Predicate disambiguation | batch_69e22701d2288190bf8676050758f172 |
completed | April 17, 2026, 12:26 p.m. |
| PDg | Predicate description generation | batch_69e24556c1348190902a4d116c3137d9 |
completed | April 17, 2026, 2:36 p.m. |
Created at: April 10, 2026, 5:09 a.m.