Triple
T4490359
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tsitska |
E107355
|
entity |
| Predicate | wineSweetnessLevel |
P16142
|
FINISHED |
| Object | typically 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: typically dry | Statement: [Tsitska, wineSweetnessLevel, typically dry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wineSweetnessLevel Context triple: [Tsitska, wineSweetnessLevel, typically dry]
-
A.
hasBitternessLevel
Indicates that an entity is associated with a specific degree or intensity of bitterness.
-
B.
isSweeterThan
Indicates that one entity has a higher level of sweetness in taste compared to another entity.
-
C.
tanninLevel
Indicates the degree or intensity of tannins present in or associated with something, typically a beverage like wine or tea.
-
D.
sweetening
Indicates the action or process of making something taste sweeter, often by adding a sweet substance.
-
E.
wineCharacteristic
chosen
Indicates a descriptive property or quality attributed to a wine, such as its flavor, aroma, color, or style.
- 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_69bd43f84f788190a1383579c4a595be |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd556d29f08190bab1e872dd7e819f |
completed | March 20, 2026, 2:10 p.m. |
| PD | Predicate disambiguation | batch_69bd5213e3d0819094b026989e686f01 |
completed | March 20, 2026, 1:56 p.m. |
Created at: March 20, 2026, 12:59 p.m.