Triple
T637666
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sauvignon Blanc |
E16660
|
entity |
| Predicate | typicalAcidity |
P2070
|
FINISHED |
| Object | high |
—
|
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 | Statement: [Sauvignon Blanc, typicalAcidity, high]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalAcidity Context triple: [Sauvignon Blanc, typicalAcidity, high]
-
A.
acidityLevel
chosen
Indicates the degree or intensity of acidity associated with an entity, typically measured by pH or a comparable scale.
-
B.
typicalIn
Indicates that something commonly occurs, appears, or is found within a given context, category, or environment.
-
C.
typicalFlavor
Indicates that something characteristically has or is associated with a particular flavor.
-
D.
typicalRange
Indicates the usual or expected range of values, conditions, or states within which something normally occurs or applies.
-
E.
typicalDegree
Indicates the usual or characteristic level, intensity, or extent to which something holds or applies in a given context.
- 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_69a4936be1c88190af56540324b57da7 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a17b125481909a6ab53424954792 |
completed | March 1, 2026, 8:28 p.m. |
| PD | Predicate disambiguation | batch_69a49d0629308190bcc137639567f7c2 |
completed | March 1, 2026, 8:09 p.m. |
Created at: March 1, 2026, 7:35 p.m.