Triple
T11427656
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miller Lite |
E270794
|
entity |
| Predicate | carbohydratesPer12oz |
P79597
|
FINISHED |
| Object | about 3.2 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: about 3.2 grams | Statement: [Miller Lite, carbohydratesPer12oz, about 3.2 grams]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: carbohydratesPer12oz Context triple: [Miller Lite, carbohydratesPer12oz, about 3.2 grams]
-
A.
carbohydratesPer12Ounces
chosen
Indicates the amount of carbohydrates contained in a 12-ounce serving of a given item.
-
B.
hasCalories
Indicates that an entity contains a specified amount of caloric energy.
-
C.
hasSugarContent
Indicates that one entity possesses or contains a specified amount or level of sugar.
-
D.
isSoftDrinkVariantOf
Indicates that one soft drink is a specific version, flavor, or formulation derived from or based on another soft drink.
-
E.
servingSizeAtOktoberfest
Indicates the typical quantity or portion in which something (such as food or drink) is served specifically at Oktoberfest.
- 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_69d6aadeef688190874bcecd88b3dd9b |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d806c000b88190bfaa646b2dc424b7 |
completed | April 9, 2026, 8:06 p.m. |
| PD | Predicate disambiguation | batch_69d7e71436f88190ac7e45a04ea5c987 |
completed | April 9, 2026, 5:51 p.m. |
Created at: April 8, 2026, 9:35 p.m.