Triple
T25637527
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Corona Light |
E642746
|
entity |
| Predicate | hasCaloriesPer12oz |
P51659
|
FINISHED |
| Object | approximately 99 calories |
—
|
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 99 calories | Statement: [Corona Light, hasCaloriesPer12oz, approximately 99 calories]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCaloriesPer12oz Context triple: [Corona Light, hasCaloriesPer12oz, approximately 99 calories]
-
A.
carbohydratesPer12Ounces
Indicates the amount of carbohydrates contained in a 12-ounce serving of a given item.
-
B.
hasCalories
chosen
Indicates that an entity contains a specified amount of caloric energy.
-
C.
hasAlcoholContent
Indicates that an entity contains alcohol and specifies the amount or concentration of that alcohol.
-
D.
isSoftDrinkVariantOf
Indicates that one soft drink is a specific version, flavor, or formulation derived from or based on another soft drink.
-
E.
isLowCalorieBeer
Indicates that a beer has a relatively low calorie content compared to typical beers.
- 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_69f67257b0448190a13011af81c81449 |
completed | May 2, 2026, 9:53 p.m. |
| PD | Predicate disambiguation | batch_69f66ec3d3d48190ab2f2b71939e572e |
completed | May 2, 2026, 9:38 p.m. |
Created at: April 21, 2026, 5:34 p.m.