Triple
T28531233
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Milk |
E722046
|
entity |
| Predicate | typicalCarbohydrateContent |
P202756
|
FINISHED |
| Object | 4.5–5% lactose for cow milk |
—
|
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: 4.5–5% lactose for cow milk | Statement: [Milk, typicalCarbohydrateContent, 4.5–5% lactose for cow milk]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalCarbohydrateContent Context triple: [Milk, typicalCarbohydrateContent, 4.5–5% lactose for cow milk]
-
A.
hasPrimaryCarbohydrate
Indicates that one entity has another entity as its main or principal carbohydrate component.
-
B.
carbohydratesPer12Ounces
Indicates the amount of carbohydrates contained in a 12-ounce serving of a given item.
-
C.
typicalFatContent
Indicates the usual or characteristic amount of fat contained in something, such as a food or product.
-
D.
limitsMacronutrient
Indicates that one entity imposes a restriction or upper bound on the amount or proportion of a specific macronutrient associated with another entity.
-
E.
calorieLevel
Indicates the relationship between an entity and the amount of calories it contains or provides, typically categorized by intensity or range (e.g., low, medium, high).
- F. None of above. chosen
Provenance (4 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_69f01a5d7ec88190ada2d5be7c06c35d |
completed | April 28, 2026, 2:24 a.m. |
| NER | Named-entity recognition | batch_6a00b6199c348190b1e90375f737d026 |
completed | May 10, 2026, 4:45 p.m. |
| PD | Predicate disambiguation | batch_6a00b5169a7881909a07167c4188731f |
completed | May 10, 2026, 4:40 p.m. |
| PDg | Predicate description generation | batch_6a00b618cb10819095ccef12d8e303c5 |
completed | May 10, 2026, 4:45 p.m. |
Created at: April 28, 2026, 3:28 a.m.