Triple
T24527331
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Okayama dialect |
E606702
|
entity |
| Predicate | geographicalVariation |
P32680
|
FINISHED |
| Object | coastal areas of Okayama Prefecture |
—
|
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: coastal areas of Okayama Prefecture | Statement: [Okayama dialect, geographicalVariation, coastal areas of Okayama Prefecture]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: geographicalVariation Context triple: [Okayama dialect, geographicalVariation, coastal areas of Okayama Prefecture]
-
A.
geographicDistribution
Indicates the spatial range or area over which something occurs, exists, or is found.
-
B.
geographicRangeType
Indicates the kind of geographic range or distribution pattern that characterizes where an entity occurs or is found.
-
C.
haveLandAreaVariation
Indicates that an entity’s land area changes over time or differs across contexts or measurements.
-
D.
geographicalUsage
Indicates that something is used, applied, or occurs within a particular geographic area or region.
-
E.
hasRegionalVariationsIn
chosen
Indicates that something exhibits different forms, versions, or characteristics depending on the geographic region.
- 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_69e2c4c85778819085f5da9af3569ad5 |
completed | April 17, 2026, 11:39 p.m. |
| NER | Named-entity recognition | batch_69f2be044d4c819094e14eda28d371a7 |
completed | April 30, 2026, 2:27 a.m. |
| PD | Predicate disambiguation | batch_69f2a6b0ca8081908d931aec560eae56 |
completed | April 30, 2026, 12:47 a.m. |
Created at: April 18, 2026, 2:25 a.m.