Triple
T34224388
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gordon's Gin |
E878006
|
entity |
| Predicate | typicalABVRegion |
P148688
|
FINISHED |
| Object | 37.5% in European markets |
—
|
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: 37.5% in European markets | Statement: [Gordon's Gin, typicalABVRegion, 37.5% in European markets]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalABVRegion Context triple: [Gordon's Gin, typicalABVRegion, 37.5% in European markets]
-
A.
beerColor
Indicates the color characteristic associated with a particular beer.
-
B.
alcoholByVolumeApprox
chosen
Indicates an approximate measurement of the proportion of alcohol by volume contained in a beverage or liquid.
-
C.
featuresAlcoholReference
Indicates that the subject includes or contains a reference to alcohol or alcoholic beverages.
-
D.
alcoholType
Indicates the specific kind or category of alcohol associated with an entity (e.g., beer, wine, spirits).
-
E.
alcoholStrengthCategory
Indicates the classification of an alcoholic beverage based on the strength or concentration of its alcohol content.
- 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_69f349b16d0481908754e3069f05e0c1 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_6a037c8ae0248190b7e2ce4bf852c22d |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379fbe4a08190bfe65ebd141164e9 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:55 a.m.