Triple
T31982681
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Graves cru classé |
E816627
|
entity |
| Predicate | grapeVarietiesInclude |
P162513
|
FINISHED |
| Object | Cabernet Sauvignon |
—
|
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 Sauvignon | Statement: [Graves cru classé, grapeVarietiesInclude, Cabernet Sauvignon]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: grapeVarietiesInclude Context triple: [Graves cru classé, grapeVarietiesInclude, Cabernet Sauvignon]
-
A.
grapeVarietyAllowed
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.
grapeVarietyType
Indicates the specific type or classification of a grape variety used or referred to in a given context.
-
C.
grapeVarietal
chosen
Indicates that one entity is a specific type or variety of grape used in wine or grape production in relation to another entity.
-
D.
alsoUsesGrapeVariety
Indicates that one entity, in addition to another, makes use of the same grape variety in its composition or production.
-
E.
linkedGrapeVariety
Indicates that there is an established relationship or association between one grape variety and another (or related grape variety entity).
- 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_69f348f6a3008190bfb59ca695fd68e2 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6b49436b0819094e21603054d05d4 |
completed | May 3, 2026, 2:36 a.m. |
| PD | Predicate disambiguation | batch_69f6b3a7bdb481908d16a32f49e38c2c |
completed | May 3, 2026, 2:32 a.m. |
Created at: May 1, 2026, 12:12 a.m.