Triple
T4490331
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tsitska |
E107355
|
entity |
| Predicate | associatedWineProfile |
P20482
|
FINISHED |
| Object | crisp |
—
|
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: crisp | Statement: [Tsitska, associatedWineProfile, crisp]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWineProfile Context triple: [Tsitska, associatedWineProfile, crisp]
-
A.
wineStylesAssociatedWith
Indicates a relationship where certain wine styles are linked or connected to a particular entity, such as a region, grape, producer, or product.
-
B.
wineReputation
Indicates the perceived quality, prestige, or standing of a wine based on expert opinion, consumer perception, or historical recognition.
-
C.
wineStructure
chosen
Indicates the overall sensory framework of a wine, encompassing how its components like acidity, tannin, body, and alcohol are balanced and interact.
-
D.
usesWineType
Indicates that one entity makes use of, incorporates, or is associated with a particular type or category of wine.
-
E.
sharesGrandCruVineyardsWith
Indicates that two entities share ownership, use, or association with the same Grand Cru–classified vineyards.
- 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.