Triple
T10815488
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Heunisch Weiss |
E255216
|
entity |
| Predicate | wineQualityReputation |
P23126
|
FINISHED |
| Object | generally low to medium quality wines |
—
|
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: generally low to medium quality wines | Statement: [Heunisch Weiss, wineQualityReputation, generally low to medium quality wines]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wineQualityReputation Context triple: [Heunisch Weiss, wineQualityReputation, generally low to medium quality wines]
-
A.
wineReputation
chosen
Indicates the perceived quality, prestige, or standing of a wine based on expert opinion, consumer perception, or historical recognition.
-
B.
wineQualityLevelProduced
Indicates the quality level or grade assigned to the wine that is produced in the described production event or process.
-
C.
wineMarket
Indicates a commercial context or marketplace where wine is bought, sold, or traded.
-
D.
wineAVA
Indicates that a wine is produced within a specific American Viticultural Area (AVA) designation.
-
E.
wineStructure
Indicates the overall sensory framework of a wine, encompassing how its components like acidity, tannin, body, and alcohol are balanced and interact.
- 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_69d6aa8081448190a9324184f2bd1c26 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d733edab248190b2cf7f7bc2684468 |
completed | April 9, 2026, 5:06 a.m. |
| PD | Predicate disambiguation | batch_69d70d1bf3648190b36fa96ea018e0dc |
completed | April 9, 2026, 2:21 a.m. |
Created at: April 8, 2026, 9:18 p.m.