Triple
T33000629
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Scansano |
E844353
|
entity |
| Predicate | wineNameDerivedFrom |
P175892
|
FINISHED |
| Object | Morello (local name for Sangiovese) |
—
|
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: Morello (local name for Sangiovese) | Statement: [Scansano, wineNameDerivedFrom, Morello (local name for Sangiovese)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wineNameDerivedFrom Context triple: [Scansano, wineNameDerivedFrom, Morello (local name for Sangiovese)]
-
A.
wineName
Indicates the specific name or designation assigned to a wine.
-
B.
wineFamily
Indicates a relationship where one wine is classified as belonging to the same broader family or style group as another wine.
-
C.
wineComponent
Indicates that one entity is a constituent ingredient or part of a wine represented by the other entity.
-
D.
wineStyle
Indicates the stylistic category or type of wine (such as its production style, sweetness, body, or other defining characteristics) associated with an entity.
-
E.
wineStructure
Indicates the overall sensory framework of a wine, encompassing how its components like acidity, tannin, body, and alcohol are balanced and interact.
- F. None of above. chosen
Provenance (4 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_69f3494e59f08190b9127c693e5c7e8f |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6d74b20a48190900dda1014cc13a8 |
completed | May 3, 2026, 5:04 a.m. |
| PD | Predicate disambiguation | batch_69f6d26f27dc8190ae426a3e1573933e |
completed | May 3, 2026, 4:43 a.m. |
| PDg | Predicate description generation | batch_69f6d749e7f081909c8196898c4191ad |
completed | May 3, 2026, 5:04 a.m. |
Created at: May 1, 2026, 1:22 a.m.