Triple
T25637701
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Corona Hard Seltzer |
E642749
|
entity |
| Predicate | fatContentClaim |
P53132
|
FINISHED |
| Object | 0 g fat |
—
|
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: 0 g fat | Statement: [Corona Hard Seltzer, fatContentClaim, 0 g fat]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fatContentClaim Context triple: [Corona Hard Seltzer, fatContentClaim, 0 g fat]
-
A.
typicalFatContent
chosen
Indicates the usual or characteristic amount of fat contained in something, such as a food or product.
-
B.
fattyAcid
Indicates a relationship where one entity is a fatty acid component, derivative, or participant in a process involving another entity.
-
C.
fatColor
Indicates the color characteristic associated with an entity’s fat or fatty tissue.
-
D.
fatStorage
Indicates the process or state in which an organism or system accumulates and retains fat as an energy reserve.
-
E.
fatDistribution
Indicates how body fat is spatially allocated or spread across different regions of an entity.
- 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_69f5fa6345548190a52498ecb0a2f555 |
completed | May 2, 2026, 1:21 p.m. |
| PD | Predicate disambiguation | batch_69f4807f8680819098a524158d049c63 |
completed | May 1, 2026, 10:29 a.m. |
Created at: April 21, 2026, 5:36 p.m.