Triple
T29803553
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prosecco |
E756776
|
entity |
| Predicate | typicalCarbonationLevel |
P84042
|
FINISHED |
| Object | spumante |
—
|
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: spumante | Statement: [Prosecco, typicalCarbonationLevel, spumante]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalCarbonationLevel Context triple: [Prosecco, typicalCarbonationLevel, spumante]
-
A.
carbonation
Indicates that a substance, typically a beverage, has been infused with carbon dioxide gas, resulting in bubbles or fizziness.
-
B.
canBeCarbonated
Indicates that the subject is capable of being made carbonated, typically by dissolving carbon dioxide under pressure.
-
C.
carbonationDescription
chosen
Indicates the description of the level, style, or characteristics of carbonation present in a beverage.
-
D.
carbonationSource
Indicates the source or method by which something becomes carbonated (i.e., how carbon dioxide is introduced).
-
E.
typicalSweetnessLevel
Indicates the usual or characteristic degree of sweetness associated with something.
- 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_69f2245584848190ad4cab1f07752ccb |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_6a02ff7de1d881909c29729f2a771381 |
completed | May 12, 2026, 10:22 a.m. |
| PD | Predicate disambiguation | batch_6a02fd1c45c48190bf9dbd91acaeee9f |
completed | May 12, 2026, 10:12 a.m. |
Created at: April 29, 2026, 5:19 p.m.