Triple
T22266222
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Caol Ila Cask Strength releases |
E550356
|
entity |
| Predicate | ABVRange |
P109725
|
FINISHED |
| Object | typically above 55% ABV |
—
|
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 above 55% ABV | Statement: [Caol Ila Cask Strength releases, ABVRange, typically above 55% ABV]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ABVRange Context triple: [Caol Ila Cask Strength releases, ABVRange, typically above 55% ABV]
-
A.
alcoholRange
chosen
Indicates the range or interval of alcohol content associated with an entity (e.g., minimum and maximum alcohol level).
-
B.
alcoholStrengthCategory
Indicates the classification of an alcoholic beverage based on the strength or concentration of its alcohol content.
-
C.
beerColor
Indicates the color characteristic associated with a particular beer.
-
D.
bottlingStrengthRange
Indicates the range of alcohol strengths at which a beverage is bottled.
-
E.
alcoholType
Indicates the specific kind or category of alcohol associated with an entity (e.g., beer, wine, spirits).
- 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_69e11e43d8208190aff4f9cf7f2c2a8a |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f141bc458c81909837373d749b915d |
completed | April 28, 2026, 11:24 p.m. |
| PD | Predicate disambiguation | batch_69e72ff0363081909f794d19c8a64837 |
completed | April 21, 2026, 8:06 a.m. |
Created at: April 16, 2026, 8:39 p.m.