Triple
T29426712
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vidal |
E746313
|
entity |
| Predicate | typicalUseInCanada |
P15483
|
FINISHED |
| Object | icewine production |
—
|
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: icewine production | Statement: [Vidal, typicalUseInCanada, icewine production]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalUseInCanada Context triple: [Vidal, typicalUseInCanada, icewine production]
-
A.
usedInCanadianProvince
Indicates that something is utilized, applied, or in operation within the jurisdiction of a Canadian province.
-
B.
usedInCountry
Indicates that something is utilized, applied, or in operation within the specified country.
-
C.
usedInCountryOrRegion
Indicates that something (such as an item, concept, or practice) is utilized or applied within a specified country or region.
-
D.
hasTypicalUsageRegion
chosen
Indicates that something is most commonly or characteristically used within a particular geographic region.
-
E.
usedInCountryType
Indicates that something is utilized or applied within a specific type or category of country (e.g., developing, industrialized, etc.).
- 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_69f0a7a06e0081908add494075912eb4 |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_6a01bb06422c819095bb42f6f3a0e801 |
completed | May 11, 2026, 11:18 a.m. |
| PD | Predicate disambiguation | batch_6a01b9991c348190ac49b65ea2fd86ed |
completed | May 11, 2026, 11:12 a.m. |
Created at: April 28, 2026, 3:09 p.m.