Triple
T36818374
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Labatt Crystal |
E909808
|
entity |
| Predicate | alcoholByVolumeApproximate |
P148688
|
FINISHED |
| Object | 5% 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: 5% ABV | Statement: [Labatt Crystal, alcoholByVolumeApproximate, 5% ABV]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: alcoholByVolumeApproximate Context triple: [Labatt Crystal, alcoholByVolumeApproximate, 5% ABV]
-
A.
alcoholByVolumeApprox
chosen
Indicates an approximate measurement of the proportion of alcohol by volume contained in a beverage or liquid.
-
B.
alcoholContentRelativeTo
Indicates that the alcohol content of one entity is compared to or expressed in relation to the alcohol content of another entity.
-
C.
alcoholStrengthCategory
Indicates the classification of an alcoholic beverage based on the strength or concentration of its alcohol content.
-
D.
featuresAlcoholReference
Indicates that the subject includes or contains a reference to alcohol or alcoholic beverages.
-
E.
beerColor
Indicates the color characteristic associated with a particular beer.
- 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_69f76e7dd13c81908c60b05adb49eeb5 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69f7ca9591e48190a5a5bdb5d72ae4b3 |
completed | May 3, 2026, 10:22 p.m. |
| PD | Predicate disambiguation | batch_69f7c89b528c8190bf80b230fc7c7108 |
completed | May 3, 2026, 10:13 p.m. |
Created at: May 3, 2026, 4:13 p.m.