Triple
T479136
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | pisco sour |
E9126
|
entity |
| Predicate | alcoholType |
P14783
|
FINISHED |
| Object | brandy-based cocktail |
—
|
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: brandy-based cocktail | Statement: [pisco sour, alcoholType, brandy-based cocktail]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: alcoholType Context triple: [pisco sour, alcoholType, brandy-based cocktail]
-
A.
traditionalDrink
Indicates that one entity is a beverage customarily consumed within the culture, heritage, or longstanding practices associated with another entity.
-
B.
servesAlcohol
Indicates that an establishment or provider offers and supplies alcoholic beverages to customers or participants.
-
C.
alcoholLevel
Indicates the measured concentration or amount of alcohol present in an entity (such as a person, substance, or environment).
-
D.
wineStyle
Indicates the stylistic category or type of wine (such as its production style, sweetness, body, or other defining characteristics) associated with an entity.
-
E.
wineColor
Indicates the color attribute or hue associated with a given wine.
- 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_69a2e7ff81708190b0507a24a997232c |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2f056459881909749764cc4a7f9e8 |
completed | Feb. 28, 2026, 1:40 p.m. |
| PD | Predicate disambiguation | batch_69a2edf1d5848190a7da27e2fddc136f |
completed | Feb. 28, 2026, 1:30 p.m. |
| PDg | Predicate description generation | batch_69a2ef4030608190b39852b347a505ca |
completed | Feb. 28, 2026, 1:36 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.