Triple
T17254877
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ondenc |
E418854
|
entity |
| Predicate | usedForWineType |
P45198
|
FINISHED |
| Object | still white wine |
—
|
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: still white wine | Statement: [Ondenc, usedForWineType, still white wine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedForWineType Context triple: [Ondenc, usedForWineType, still white wine]
-
A.
usesWineType
Indicates that one entity makes use of, incorporates, or is associated with a particular type or category of wine.
-
B.
wineVariety
Indicates the specific type or variety of wine associated with an entity.
-
C.
regulatesWineType
Indicates that one entity has authority or influence over the rules, standards, or conditions governing a particular type of wine.
-
D.
wineStylesAssociatedWith
Indicates a relationship where certain wine styles are linked or connected to a particular entity, such as a region, grape, producer, or product.
-
E.
primaryGrapeUse
chosen
Indicates that a grape variety is primarily used for a particular purpose, such as winemaking, table consumption, or raisin production.
- 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_69d886d9ab108190b70edd8d17aa1204 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42e6c362c819088965c6e05f33faf |
completed | April 19, 2026, 1:22 a.m. |
| PD | Predicate disambiguation | batch_69e3832a284481908a8a3da7ac91de5a |
completed | April 18, 2026, 1:12 p.m. |
Created at: April 10, 2026, 5:39 a.m.