Triple
T30153716
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yuki Suzuki |
E766464
|
entity |
| Predicate | frequencyOfSurname |
P122732
|
FINISHED |
| Object | Suzuki is a common Japanese surname |
—
|
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: Suzuki is a common Japanese surname | Statement: [Yuki Suzuki, frequencyOfSurname, Suzuki is a common Japanese surname]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: frequencyOfSurname Context triple: [Yuki Suzuki, frequencyOfSurname, Suzuki is a common Japanese surname]
-
A.
hasSurnameFrequency
chosen
Indicates that a surname occurs with a specified frequency or rate within a given population or dataset.
-
B.
hasGivenNameFrequency
Indicates the frequency or commonness with which a particular given name occurs within a specified population or context.
-
C.
hasApproximateNumberOfSurnames
Indicates that an entity is associated with an estimated or approximate count of surnames rather than an exact number.
-
D.
isAmongMostCommonSurnamesIn
Indicates that a surname ranks within the group of most frequently occurring surnames in a specified region or population.
-
E.
hasSurnameFrequencyReason
Indicates the reason or explanation for the frequency with which a particular surname occurs.
- 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_69f22479cd088190ab4c6f3fce39d1c5 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f68f670b608190a0b6ab60d722b4e0 |
completed | May 2, 2026, 11:57 p.m. |
| PD | Predicate disambiguation | batch_69f68b7b03488190b1db5fde4c7dd6e5 |
completed | May 2, 2026, 11:40 p.m. |
Created at: April 29, 2026, 7:20 p.m.