Triple
T22517412
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ABC Extra Stout |
E556683
|
entity |
| Predicate | hasAlcoholContent |
P148696
|
FINISHED |
| Object | higher than standard lagers |
—
|
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: higher than standard lagers | Statement: [ABC Extra Stout, hasAlcoholContent, higher than standard lagers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAlcoholContent Context triple: [ABC Extra Stout, hasAlcoholContent, higher than standard lagers]
-
A.
hasAlcoholicVariant
Indicates that an entity has a related version or counterpart that contains alcohol.
-
B.
isAlcoholicBeverage
Indicates that a beverage contains alcohol and is classified as an alcoholic drink.
-
C.
hasAlcoholTheme
Indicates that the subject involves, features, or is centered around alcohol-related content or themes.
-
D.
madeWithAlcohol
Indicates that something is created, prepared, or produced using alcohol as an ingredient or component.
-
E.
alcoholType
Indicates the specific kind or category of alcohol associated with an entity (e.g., beer, wine, spirits).
- 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_69e11e5657e881909f16ca58352c50da |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15e2df59c81909c4ae2f20f1cbb32 |
completed | April 29, 2026, 1:26 a.m. |
| PD | Predicate disambiguation | batch_69ee625e3b408190a60c759fb0b28fe2 |
completed | April 26, 2026, 7:07 p.m. |
| PDg | Predicate description generation | batch_69ee8841e9cc81908d23b34215e3be71 |
completed | April 26, 2026, 9:48 p.m. |
Created at: April 16, 2026, 8:50 p.m.