Triple
T32239765
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | San Pietro in Cariano |
E823576
|
entity |
| Predicate | hasWineTypeProduced |
P26509
|
FINISHED |
| Object | Valpolicella Classico |
—
|
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: Valpolicella Classico | Statement: [San Pietro in Cariano, hasWineTypeProduced, Valpolicella Classico]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWineTypeProduced Context triple: [San Pietro in Cariano, hasWineTypeProduced, Valpolicella Classico]
-
A.
hasWineryType
Indicates the specific category or classification of winery associated with an entity.
-
B.
producesWine
chosen
Indicates that one entity creates or manufactures wine as a product.
-
C.
hasWineCategory
Indicates that one entity is classified under, or associated with, a particular category or type of wine.
-
D.
usesWineType
Indicates that one entity makes use of, incorporates, or is associated with a particular type or category of wine.
-
E.
hasWinemakingOption
Indicates that an entity offers or includes a particular method, feature, or configuration related to winemaking.
- 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_69f3490c140481908ed53b98b561eaa1 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f727afd5d88190ad48735cd1b32787 |
completed | May 3, 2026, 10:47 a.m. |
| PD | Predicate disambiguation | batch_69f72737c42c8190a3f781a5e98868ff |
completed | May 3, 2026, 10:45 a.m. |
Created at: May 1, 2026, 12:39 a.m.