Triple
T10330913
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clairette de Die wine |
E242869
|
entity |
| Predicate | carbonationSource |
P93464
|
FINISHED |
| Object | natural fermentation in bottle |
—
|
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: natural fermentation in bottle | Statement: [Clairette de Die wine, carbonationSource, natural fermentation in bottle]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: carbonationSource Context triple: [Clairette de Die wine, carbonationSource, natural fermentation in bottle]
-
A.
carbonation
Indicates that a substance, typically a beverage, has been infused with carbon dioxide gas, resulting in bubbles or fizziness.
-
B.
carbonationDescription
Indicates the description of the level, style, or characteristics of carbonation present in a beverage.
-
C.
hasCarbonatedWater
Indicates that an entity contains or is associated with carbonated (fizzy) water as a component or ingredient.
-
D.
carbonSource
Indicates that one entity serves as the source or provider of carbon for another entity or process.
-
E.
isSoftDrinkVariantOf
Indicates that one soft drink is a specific version, flavor, or formulation derived from or based on another soft drink.
- F. None of above. chosen
Provenance (4 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_69d381af787481908bc401325c760a88 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d7fb77348190ac8ff887f6f03450 |
completed | April 7, 2026, 10:10 a.m. |
| PD | Predicate disambiguation | batch_69d4d1f760e88190abea6dcc4f04f2c1 |
completed | April 7, 2026, 9:44 a.m. |
| PDg | Predicate description generation | batch_69d4d7cada7881908beba55a1dc9ecb9 |
completed | April 7, 2026, 10:09 a.m. |
Created at: April 6, 2026, 11:52 a.m.