Triple
T33012771
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anjou-Villages |
E844688
|
entity |
| Predicate | allowedGrapeVariety |
P37246
|
FINISHED |
| Object | Cabernet Franc |
—
|
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: Cabernet Franc | Statement: [Anjou-Villages, allowedGrapeVariety, Cabernet Franc]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: allowedGrapeVariety Context triple: [Anjou-Villages, allowedGrapeVariety, Cabernet Franc]
-
A.
grapeVarietyAllowed
chosen
Indicates that a specific grape variety is permitted or authorized for use in a given context, such as a wine, region, or product specification.
-
B.
alsoUsesGrapeVariety
Indicates that one entity, in addition to another, makes use of the same grape variety in its composition or production.
-
C.
grapeVarietal
Indicates that one entity is a specific type or variety of grape used in wine or grape production in relation to another entity.
-
D.
grapeVarietyType
Indicates the specific type or classification of a grape variety used or referred to in a given context.
-
E.
wineTypeAllowed
Indicates that a particular type of wine is permitted or acceptable in a given context or for a given purpose.
- 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_69f3494f3b4081909dccf2af34372a26 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fcab6e888881908ca9e18660928a40 |
completed | May 7, 2026, 3:10 p.m. |
| PD | Predicate disambiguation | batch_69fc4562a5b88190bad48f083a6dcdfa |
completed | May 7, 2026, 7:55 a.m. |
Created at: May 1, 2026, 1:23 a.m.