Triple
T22919305
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Caffeine-Free Diet Pepsi |
E568813
|
entity |
| Predicate | sugar |
P112699
|
FINISHED |
| Object | 0 g per serving |
—
|
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 per serving | Statement: [Caffeine-Free Diet Pepsi, sugar, 0 g per serving]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sugar Context triple: [Caffeine-Free Diet Pepsi, sugar, 0 g per serving]
-
A.
sweetening
Indicates the action or process of making something taste sweeter, often by adding a sweet substance.
-
B.
sweetenerType
Indicates the specific kind or category of sweetener associated with or used in relation to an entity.
-
C.
sugarContentCategory
chosen
Indicates the classification of something based on how much sugar it contains (e.g., low, medium, or high sugar content).
-
D.
isSugarFree
Indicates that something does not contain sugar or has been formulated without added sugar.
-
E.
sweetenerVariant
Indicates that one sweetening agent is a specific type, version, or alternative form of another sweetening agent.
- 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_69e2458d90c88190a58cead4e781ca6a |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f180d316188190901d9356c07110e3 |
completed | April 29, 2026, 3:53 a.m. |
| PD | Predicate disambiguation | batch_69ef3b7c5fc081909ac50c5c8569cc19 |
completed | April 27, 2026, 10:33 a.m. |
Created at: April 17, 2026, 3:42 p.m.