Triple
T28124967
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bud Light Lime |
E710901
|
entity |
| Predicate | hasCalorieContentPer12oz |
P51659
|
FINISHED |
| Object | approximately 116 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 116 calories | Statement: [Bud Light Lime, hasCalorieContentPer12oz, approximately 116 calories]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCalorieContentPer12oz Context triple: [Bud Light Lime, hasCalorieContentPer12oz, approximately 116 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.
hasSugarContent
Indicates that one entity possesses or contains a specified amount or level of sugar.
-
E.
hasNutrientContent
Indicates that one entity contains or provides a specified amount or type of nutrient relative to another entity or standard.
- 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_69ef9b73bd288190a21ae3d6aa14f386 |
completed | April 27, 2026, 5:22 p.m. |
| NER | Named-entity recognition | batch_69fba78aca4c8190b8f1831e8cc04e06 |
completed | May 6, 2026, 8:41 p.m. |
| PD | Predicate disambiguation | batch_69fba34a65a4819088bac6c17542d71c |
completed | May 6, 2026, 8:23 p.m. |
Created at: April 27, 2026, 9:19 p.m.