Triple
T25637528
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Corona Light |
E642746
|
entity |
| Predicate | hasCarbohydratesPer12oz |
P79597
|
FINISHED |
| Object | approximately 5 grams |
—
|
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: approximately 5 grams | Statement: [Corona Light, hasCarbohydratesPer12oz, approximately 5 grams]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCarbohydratesPer12oz Context triple: [Corona Light, hasCarbohydratesPer12oz, approximately 5 grams]
-
A.
carbohydratesPer12Ounces
chosen
Indicates the amount of carbohydrates contained in a 12-ounce serving of a given item.
-
B.
containsSugarAlcohols
Indicates that the item includes one or more sugar alcohol compounds as part of its composition.
-
C.
hasSugarContent
Indicates that one entity possesses or contains a specified amount or level of sugar.
-
D.
hasPrimaryCarbohydrate
Indicates that one entity has another entity as its main or principal carbohydrate component.
-
E.
hasAlcoholContent
Indicates that an entity contains alcohol and specifies the amount or concentration of that alcohol.
- 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_69e77e7ce28081908b08d65ee6e5c8be |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f674e06c9481909ed0ea736408f0d7 |
completed | May 2, 2026, 10:04 p.m. |
| PD | Predicate disambiguation | batch_69f673c2f81c8190bf369226306eef09 |
completed | May 2, 2026, 9:59 p.m. |
Created at: April 21, 2026, 5:34 p.m.