Triple
T36274689
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Japanese cuisine |
E892771
|
entity |
| Predicate | notableRegionalVariant |
P11942
|
FINISHED |
| Object | Kansai cuisine |
—
|
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: Kansai cuisine | Statement: [Japanese cuisine, notableRegionalVariant, Kansai cuisine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableRegionalVariant Context triple: [Japanese cuisine, notableRegionalVariant, Kansai cuisine]
-
A.
regionalVariantOf
chosen
Indicates that one entity is a version or form of another that is specific to a particular geographic region or locale.
-
B.
hasRegionalVariationsIn
Indicates that something exhibits different forms, versions, or characteristics depending on the geographic region.
-
C.
linguisticVariant
Indicates that one linguistic form is an alternative version or expression of another within the same or closely related language context.
-
D.
notableDialect
Indicates that an entity is recognized for having a distinct or noteworthy dialect associated with it.
-
E.
regionalDialect
Indicates that one entity uses or is associated with a dialect specific to a particular geographic region in relation to another entity.
- 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_69f76e488f34819083e254dbe288c27a |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a037c8d06cc8190ab6a5e18d9d2571e |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a0a54cc8190868c1bfa1590d1a6 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:09 p.m.