Triple
T36979210
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tinta de Toro |
E914777
|
entity |
| Predicate | typicalUseInBlend |
P56866
|
FINISHED |
| Object | varietal wines |
—
|
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: varietal wines | Statement: [Tinta de Toro, typicalUseInBlend, varietal wines]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalUseInBlend Context triple: [Tinta de Toro, typicalUseInBlend, varietal wines]
-
A.
usedInBlends
chosen
Indicates that something serves as an ingredient or component within one or more mixtures, combinations, or blends.
-
B.
hasBlendOf
Indicates that something is composed of or contains a mixture of multiple specified components or elements.
-
C.
typicalBlendStyle
Indicates the usual or characteristic way in which two or more elements are combined or mixed together.
-
D.
blendsForm
Indicates that one entity is a mixture or combination of the forms or characteristics of another entity.
-
E.
notableBlendStyle
Indicates a characteristic way in which elements are combined or mixed that is particularly distinctive or noteworthy.
- 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_69f76e8d13b4819089af24a47ce092fc |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a037c8e2c648190a65fc9c7872861af |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a10036481909c71188b2a0e7f04 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:14 p.m.