Triple
T31933842
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Furmint |
E815330
|
entity |
| Predicate | keyWineCharacteristic |
P16142
|
FINISHED |
| Object | high acidity |
—
|
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: high acidity | Statement: [Furmint, keyWineCharacteristic, high acidity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: keyWineCharacteristic Context triple: [Furmint, keyWineCharacteristic, high acidity]
-
A.
wineCharacteristic
chosen
Indicates a descriptive property or quality attributed to a wine, such as its flavor, aroma, color, or style.
-
B.
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.
-
C.
viticulturalCharacteristic
Indicates a relationship where a specific trait, quality, or property is attributed to viticulture or grape-growing practices.
-
D.
wineStyleContribution
Indicates how much a given factor or component influences or shapes the overall style or character of a wine.
-
E.
winePairing
Indicates a relationship where a particular wine is recommended as a suitable accompaniment for a given food or dish.
- 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_69f348f3035c81908558e2339955abb3 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6b239024c81909c3b411b0bff1cbc |
completed | May 3, 2026, 2:26 a.m. |
| PD | Predicate disambiguation | batch_69f6aca7081881909e96a8b05ec086bb |
completed | May 3, 2026, 2:02 a.m. |
Created at: May 1, 2026, 12:04 a.m.