Triple
T14203216
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Usakhelauri grape |
E352015
|
entity |
| Predicate | wineSweetnessProfile |
P62205
|
FINISHED |
| Object | semi-sweet |
—
|
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: semi-sweet | Statement: [Usakhelauri grape, wineSweetnessProfile, semi-sweet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wineSweetnessProfile Context triple: [Usakhelauri grape, wineSweetnessProfile, semi-sweet]
-
A.
typicalSweetnessLevel
chosen
Indicates the usual or characteristic degree of sweetness associated with something.
-
B.
wineCharacteristic
Indicates a descriptive property or quality attributed to a wine, such as its flavor, aroma, color, or style.
-
C.
hasTastingProfile
Indicates that an entity possesses a specific flavor or sensory profile, typically describing its characteristic tastes and aromas.
-
D.
wineAcidityType
Indicates the type or category of acidity associated with a given wine.
-
E.
sweetWinePermitted
Indicates that the consumption or use of sweet wine is allowed under the specified conditions or rules.
- 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_69d827894ac0819097803e57f3227b23 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de61f589a08190b71ad4e69d92ffd0 |
completed | April 14, 2026, 3:49 p.m. |
| PD | Predicate disambiguation | batch_69de05bcd7d48190a4848d9320404aa6 |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 10, 2026, 1:05 a.m.