Triple
T34569906
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Neuburger |
E887596
|
entity |
| Predicate | typicalWineTexture |
P54672
|
FINISHED |
| Object | creamy |
—
|
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: creamy | Statement: [Neuburger, typicalWineTexture, creamy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalWineTexture Context triple: [Neuburger, typicalWineTexture, creamy]
-
A.
wineCharacteristic
Indicates a descriptive property or quality attributed to a wine, such as its flavor, aroma, color, or style.
-
B.
wineStyle
Indicates the stylistic category or type of wine (such as its production style, sweetness, body, or other defining characteristics) associated with an entity.
-
C.
grapeVarietal
Indicates that one entity is a specific type or variety of grape used in wine or grape production in relation to another entity.
-
D.
wineTexture
chosen
Indicates the perceived tactile quality or mouthfeel of a wine, such as how smooth, rough, light, or heavy it feels when tasted.
-
E.
grapeVarietyType
Indicates the specific type or classification of a grape variety used or referred to 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_69f349d1a5fc81908557a46875b2f157 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_6a037c8ae0248190b7e2ce4bf852c22d |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379fd7aac8190873077e63873aa72 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 2:02 a.m.