Triple
T37625465
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Old Fitzgerald |
E936193
|
entity |
| Predicate | hasMinimumABV |
P121997
|
FINISHED |
| Object | 40% ABV (standard bottlings) |
—
|
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: 40% ABV (standard bottlings) | Statement: [Old Fitzgerald, hasMinimumABV, 40% ABV (standard bottlings)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMinimumABV Context triple: [Old Fitzgerald, hasMinimumABV, 40% ABV (standard bottlings)]
-
A.
higherMinimumAlcoholThan
Indicates that the minimum required or actual alcohol content of one entity is greater than that of another entity.
-
B.
minimumAlcoholPotential
Indicates the lowest level of potential alcohol content that is required or allowed in a given context or product.
-
C.
minimumAlcohol
chosen
Indicates that there is a specified minimum amount or concentration of alcohol required or present in the described context.
-
D.
hasAlcoholContent
Indicates that an entity contains alcohol and specifies the amount or concentration of that alcohol.
-
E.
alcoholByVolumeApprox
Indicates an approximate measurement of the proportion of alcohol by volume contained in a beverage or liquid.
- 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_69f76ed24820819081bafd36e9088701 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fd783fed9c81909e792702636c4f1f |
completed | May 8, 2026, 5:44 a.m. |
| PD | Predicate disambiguation | batch_69fd7788e63c81909de22fdafcfe41c0 |
completed | May 8, 2026, 5:41 a.m. |
Created at: May 3, 2026, 4:18 p.m.