Triple
T6809877
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dolcetto |
E156601
|
entity |
| Predicate | bitternessNote |
P38317
|
FINISHED |
| Object | slight almond bitterness |
—
|
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: slight almond bitterness | Statement: [Dolcetto, bitternessNote, slight almond bitterness]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bitternessNote Context triple: [Dolcetto, bitternessNote, slight almond bitterness]
-
A.
hasBitternessLevel
chosen
Indicates that an entity is associated with a specific degree or intensity of bitterness.
-
B.
tanninLevel
Indicates the degree or intensity of tannins present in or associated with something, typically a beverage like wine or tea.
-
C.
allowsTastingOf
Indicates that one entity permits another entity to sample or try the taste of something.
-
D.
wineCharacteristic
Indicates a descriptive property or quality attributed to a wine, such as its flavor, aroma, color, or style.
-
E.
mouthfeel
Indicates the sensory qualities and physical sensations a substance produces in the mouth when consumed.
- 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_69c68828b26c819090fe9df7612bbc27 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d30c741881909e220b05aa564bc2 |
completed | March 27, 2026, 6:57 p.m. |
| PD | Predicate disambiguation | batch_69c6d09bb4f881909bf20c188cb3e8e1 |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:16 p.m.