Triple
T5179170
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gewürztraminer wine |
E116874
|
entity |
| Predicate | typicalSweetnessLevel |
P62205
|
FINISHED |
| Object | off-dry |
—
|
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: off-dry | Statement: [Gewürztraminer wine, typicalSweetnessLevel, off-dry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalSweetnessLevel Context triple: [Gewürztraminer wine, typicalSweetnessLevel, off-dry]
-
A.
sweetening
Indicates the action or process of making something taste sweeter, often by adding a sweet substance.
-
B.
isSweeterThan
Indicates that one entity has a higher level of sweetness in taste compared to another entity.
-
C.
typicalFlavor
Indicates that something characteristically has or is associated with a particular flavor.
-
D.
traditionalSweet
Indicates that something is a sweet food or dessert prepared according to long-established customs or cultural traditions.
-
E.
hasBitternessLevel
Indicates that an entity is associated with a specific degree or intensity of bitterness.
- F. None of above. chosen
Provenance (4 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_69bd446140f08190becb93c61158f27f |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd79978a208190b2e5909795108327 |
completed | March 20, 2026, 4:45 p.m. |
| PD | Predicate disambiguation | batch_69bd77b529948190b86671ebe43f4734 |
completed | March 20, 2026, 4:37 p.m. |
| PDg | Predicate description generation | batch_69bd79251b548190918a1eb930e24c22 |
completed | March 20, 2026, 4:43 p.m. |
Created at: March 20, 2026, 1:45 p.m.