Triple
T27940107
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | American wine industry |
E700717
|
entity |
| Predicate | majorWineStyle |
P55208
|
FINISHED |
| Object | still 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 wine | Statement: [American wine industry, majorWineStyle, still wine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: majorWineStyle Context triple: [American wine industry, majorWineStyle, still wine]
-
A.
wineStyle
Indicates the stylistic category or type of wine (such as its production style, sweetness, body, or other defining characteristics) associated with an entity.
-
B.
wineStyleContribution
Indicates how much a given factor or component influences or shapes the overall style or character of a wine.
-
C.
wineStylesAssociatedWith
chosen
Indicates a relationship where certain wine styles are linked or connected to a particular entity, such as a region, grape, producer, or product.
-
D.
wineVariety
Indicates the specific type or variety of wine associated with an entity.
-
E.
wineSpeciality
Indicates that an entity (such as a person, place, or establishment) is particularly known for, focused on, or distinguished by a specific type or aspect of wine.
- 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_69ef6a5028108190a14696d9821dde49 |
completed | April 27, 2026, 1:53 p.m. |
| NER | Named-entity recognition | batch_69fd0b92f42881908cd77e3f058adcc2 |
completed | May 7, 2026, 10 p.m. |
| PD | Predicate disambiguation | batch_69fd0a3d68d4819094d92040f7c48d7c |
completed | May 7, 2026, 9:55 p.m. |
Created at: April 27, 2026, 7:17 p.m.